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Speaker 1: Happy Monday, and welcome to another episode of the Chuck Podcast.

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Speaker 1: So here we are. It is Independent's birthday week for America,

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Speaker 1: and wow, do we have a lot of things to

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Speaker 1: talk about before we get to the actual two hundred

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Speaker 1: and forty ninth birthday. I'll be coming at you at

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Speaker 1: least one more time before before our two hundred and

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Speaker 1: forty ninth birthday. But we have a big week before

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Speaker 1: everybody leaves Washington to celebrate said two hundred and forty

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Speaker 1: ninth birthday. But you know, we don't look a day

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Speaker 1: over two hundred and forty seven, do we? But I digress.

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Speaker 1: Look the big news obviously in many ways. Politically, yes,

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Speaker 1: you have the President trying to trying to just jam

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Speaker 1: through whatever bill he can get out of Congress. And

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Speaker 1: I got a lot to say about how that's working out.

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Speaker 1: It's not going to be working out so well politically.

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Speaker 1: And how do we know, because we had a gigantic

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Speaker 1: announcement that has shaken up the battle for control of

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Speaker 1: the Senate in twenty twenty six. Tom tillis Republican Senator

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Speaker 1: from North Carolina. Two Termer got elected in twenty fourteen,

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Speaker 1: ousting an incumbent Democrat at the time has decided not

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Speaker 1: to seek reelection. Now he's been decidedly non maga. That

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Speaker 1: goes back to the first term, and he was somebody

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Speaker 1: that publicly challenged Donald Trump in his first term a

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Speaker 1: couple of times, didn't go all the way into voting

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Speaker 1: to convict Donald Trump like his then partner in the

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Speaker 1: US Senate, Richard Byrd did, who was one of the

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Speaker 1: people devoted to convict him after the second impeachment. But

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Speaker 1: Tom Tillis did push back, particularly on the president's overuse

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Speaker 1: of national emergencies in order to usurp power from Congress.

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Speaker 1: And we saw all year long as soon as Trump

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Speaker 1: got into office. Tillis has been because it's a reelection

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Speaker 1: year number one, but he's been sort of one of

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Speaker 1: the skeptical Republicans struggling to rally around Trump. He was

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Speaker 1: always trying to get there, whether it was on personnel.

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Speaker 1: Pete Hegseth was going to vote against Pete Haigseth and

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Speaker 1: the harassment that he faced, that his family faced, just

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Speaker 1: like what happened to Joni Ernst when her when she

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Speaker 1: was attacked when it looked like she was going to

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Speaker 1: come out against Hag Seth. It has left a mark

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Speaker 1: on many of these Republican senators. The way when maga,

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Speaker 1: excuse me, when Donald Trump in his political team sort

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Speaker 1: of point a finger and say you're not maga. Whoever

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Speaker 1: it is right in the moment. Look what's happening to

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Speaker 1: Thomas Massey right when they point a finger and then

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Speaker 1: it's sort of like, you know, pounce, right, it's sending

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Speaker 1: a signal to the masses to pounce. The harassment is

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Speaker 1: at incredible levels. There are some stories that I understand.

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Speaker 1: I'm going to be careful here because some of this

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Speaker 1: stuff is off the record information that I've gotten, so

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Speaker 1: I don't want to violate that aspect of it. But

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Speaker 1: Tom Tillis didn't. This wasn't the well the first time

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Speaker 1: he felt threatened in harassed by Team Trump. Right, obviously

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Speaker 1: Donald Trump himself. As soon as Tom Tillis was one

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Speaker 1: of the senators who decided not to vote to advance

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Speaker 1: this bill, and he made it clear he's going to

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Speaker 1: vote against it, Donald Trump said he's talking to any

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Speaker 1: and all primary challengers, and he targeted him on True's

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Speaker 1: social and within twenty four hours, Tillis is announcing he's

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Speaker 1: not seeking reelection at all. The point is this was

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Speaker 1: years in the making, not days in the making, and

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Speaker 1: not even months in the making. And he's not alone.

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Speaker 1: Ask Jeff Flake what it was like to oppost Donald Trump?

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Speaker 1: Asked Bob Corker what it was like to oppost Donald Trump.

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Speaker 1: Those are two Republican senators who nobody thought of as

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Speaker 1: liberal Republicans back when they were in the United States

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Speaker 1: Senate in that first term, who both left rather than

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Speaker 1: and decided to retire rather than face try to face

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Speaker 1: off against Trump and a Trump backed primary. And many

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Speaker 1: have seen that that is that is not an easy

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Speaker 1: thing to do. Some you can sometimes beat it back.

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Speaker 1: A few have beat back Trump back primaries.

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Speaker 2: But it's not easy.

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Speaker 1: And even if you win, it's sort of a pureic

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Speaker 1: victory because once you get back to Washington, nobody wants

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Speaker 1: to touch you. Right, David Valdeo, he's the last remaining

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Speaker 1: I think he think he's one of two House members

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Speaker 1: remaining who voted to convict, voted to impeach in the.

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Speaker 2: House Donald Trump.

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Speaker 1: And it's not as if other Republicans race to go

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Speaker 1: co sponsor bills with him. You know, once you have

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Speaker 1: the skeptical Trump stank on you let alone never Trump stank, right,

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Speaker 1: but the skeptical Trump that you want to be an independent,

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Speaker 1: that's it, right, it is. It is hard to recover

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Speaker 1: from that. In many ways, Tom Tillis's statement seemed to

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Speaker 1: indicate that this was years in the making. He said

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Speaker 1: the following and Washington, over the last few years, it's

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Speaker 1: become increasingly evident that leaders who are willing to embrace bipartisanship, compromise,

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Speaker 1: and demonstrate independent thinking are becoming an endangered species independent thinking.

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Speaker 1: It's interesting to me that he chose not to try

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Speaker 1: to run as an independent. North Carolina not a very

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Speaker 1: friendly state to getting on the ballot as a third

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Speaker 1: party or as an independent candidate. So perhaps it's understandable,

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Speaker 1: and this is he was. He was a Republican through

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Speaker 1: and through. He was the Assembly speaker when he ran

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Speaker 1: for the usn AT in twenty fourteen. He was a

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Speaker 1: party man. This is not somebody who's always been a

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Speaker 1: quote unquote liberal Republican, maverick, Republican, libertarian, whatever you wanted

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Speaker 1: to depict him. He was a mainstream conservative Republican. But

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Speaker 1: as we've seen, whether you're Romney, whether you're you know,

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Speaker 1: he's I would argue, more conservative than at Don Bacon. Right.

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Speaker 1: Don Bacon, who has also chosen his retirement, is an

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Speaker 1: odd way even more understandable given the situation he's been in.

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Speaker 1: He's sort of exhausted from always having to run against

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Speaker 1: his party in order to win reelection. Now he's done

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Speaker 1: it a bunch of times, right, and he somehow hasn't

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Speaker 1: gotten the full wrath of Trump World. It's as if

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Speaker 1: enough House Republicans went to Trump's scheme and said, hey,

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Speaker 1: lay off the guy, because if you get rid of them,

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Speaker 1: we can't win that seat, which I think Republicans are

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Speaker 1: about to find out now that Don Bacon is not

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Speaker 1: running there. But the Tillis move is a big deal

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Speaker 1: because Democrats have been trying to get Roy Cooper, the

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Speaker 1: recently retired or term limited governor out of North Carolina,

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Speaker 1: to run in that race, and there's been some hesitation.

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Speaker 1: Now some of the speculation is that it was hesitating

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Speaker 1: because Cooper would like to run for president. And I

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Speaker 1: do think Cooper would like to run for president. But

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Speaker 1: the question is whether Cooper could find a lane. Is

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Speaker 1: he you know, while he's not in his seventies or eighties,

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Speaker 1: he's certainly getting closer to that age than he is

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Speaker 1: Gen X or millennial, and so there is some question

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Speaker 1: about whether he could fully rally the troops. But I

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Speaker 1: think what really was an obstacle for Cooper was the

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Speaker 1: fact that he thought Tillos would probably survive a primary challenge. Right.

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Speaker 1: The Mark Robinson debacle in the North Carolina governor's race

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Speaker 1: in twenty twenty four really sort of set back MAGA

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Speaker 1: in the state of North Carolina. So I actually they

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Speaker 1: till Us before this, before his decision to oppose President

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Speaker 1: Trump's agenda, if he had somehow you know, it pulled

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Speaker 1: a Cornin right. But Cornyn's doing right. So John Cornan

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Speaker 1: is trying to be just mega enough to not invite

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Speaker 1: the attacks of MAGA. I don't think it's obviously not working.

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Speaker 1: We've seen all the polling in Texas. Ken Paxton, the

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Speaker 1: very mega attorney general there double digit leads and just

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Speaker 1: about every repole any poll that I've seen conducted, whether

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Speaker 1: no matter of the methodology. So it's pretty clear that

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Speaker 1: Cornyn it may not. There's he may never be able

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Speaker 1: to prove his MAGA enough and that Paxton is a

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Speaker 1: is a much better MAGA challenger to Cornyn than say

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Speaker 1: Mark Robinson, the ethically and character plagued candidate that ended

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Speaker 1: up essentially getting out or of you know, handed the

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Speaker 1: governor's mansion to the Democrats, and that attorney general there,

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Speaker 1: so a former churning general now the governor. And so

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Speaker 1: now I think Cooper's more likely to run right now

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Speaker 1: that it's an open seat, and now that you're likely

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Speaker 1: to have a Republican nominee that will be decidedly to

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Speaker 1: the right of Tillis, And it's going to be interesting

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Speaker 1: to see that you're gonna have Tillis's voting record still,

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Speaker 1: and now that Tillis isn't running, he's going to be

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Speaker 1: more inclined to vote against the Trump agenda, and he's

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Speaker 1: going to feel safer, almost freer to say what he wants,

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Speaker 1: you know, kind of like a journalist who no longer

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Speaker 1: works for a corporate own network, feeling as if they

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Speaker 1: can say everything that they've been wanting to say and

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Speaker 1: don't have to worry about sort of rounding the edges,

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Speaker 1: if you will. And I think that that's going to

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Speaker 1: be the Tillis voting record. While the twenty twenty six

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Speaker 1: campaign is going on and then you're going to have

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Speaker 1: my guess as a maga Republican primary that Tillos right,

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Speaker 1: all the different candidates will try to say, hey, I'm

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Speaker 1: not Tillis, you know, in order to somehow get the

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Speaker 1: bona fides and get Trump's endorsement if it becomes a

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Speaker 1: battle for Trump's endorsement, unless, of course, somebody named Trump

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Speaker 1: decides to jump in the race. Laura Trump, who was

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Speaker 1: sort of flirting with that race a couple of years ago,

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Speaker 1: not with that one, but back when Richard Burr decided

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Speaker 1: not to seek reelection, then decided not to Then there

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Speaker 1: was the Florida Senate appointment that she clearly was trying

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Speaker 1: to get and DeSantis decided to block her there. She

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Speaker 1: is a North Carolina native. And again, there are no

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Speaker 1: residency requirements with senate. I mean literally, you spend a

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Speaker 1: day in a state, you can become the senator. Governor's different.

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Speaker 1: Usually most states require three, five or seven years residency

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Speaker 1: before you can actually run for the run for governor.

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Speaker 1: But you can literally you don't even have to live

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Speaker 1: in the state full time. That's Tommy Tupperville. It's not

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Speaker 1: clear he lived in the state of Alabama until after

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Speaker 1: he won a Senate see the first time. But that's

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Speaker 1: the rules. So you know, whether you can hate it

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Speaker 1: and all that stuff, and you know, a good candidate,

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Speaker 1: a good challenger will bring it up. Then the voters

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Speaker 1: will make that decision. So if Lord Trump's on the

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Speaker 1: I don't see how that's very helpful to the Republicans

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Speaker 1: for what it is. Maybe it avoids a messic primary,

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Speaker 1: but you'll literally have Trump on the ballot in a

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Speaker 1: midterm year that's likely to be a referendum on Trump. Uh.

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Speaker 1: And I am I am very skeptical that that is

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Speaker 1: a good idea for the Republican Party. Whatever you It

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Speaker 1: just feels like that is that is, that is extra

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Speaker 1: baggage and extra saddling on there. So here you're going

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Speaker 1: to have this. So I do expect Cooper now to

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Speaker 1: get in. It's an open seat, it's much easier. He

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Speaker 1: knows his opponent is going to be to the right

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Speaker 1: of Tillis hard stop. That makes the race a thousand

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Speaker 1: times more appealing than it was before when there was

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Speaker 1: tell Us a really good politician, and I can understand

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Speaker 1: why Cooper may have been hesitant to jump in there.

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Speaker 1: I don't think you'll see that hesitation anymore.

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Speaker 3: So.

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Speaker 1: North Carolina in play. So the last time a Donald

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Speaker 1: Trump essentially pushed out a swing state Republican senator, you

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Speaker 1: could argue, was Jeff Flake. How that turned out. There's

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Speaker 1: now two Democratic senators in the state of Arizona since

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Speaker 1: Donald Trump got elected. It's been interesting to watch Donald

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Speaker 1: Trump is for some of these swing states. He's been

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Speaker 1: an allergy. Right, Arizona now is two Democratic senators. Georgia

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Speaker 1: now has two Democratic senators. Neither state had democratic neither

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Speaker 1: state had one Democratic senator, I think until until Donald

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Speaker 1: Trump showed up. So now that said, Florida obviously has

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Speaker 1: gotten decidedly more wrecked. So that was something a few

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Speaker 1: of these swing states he has pushed.

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Speaker 2: In the other direction. But you still you still have two.

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Speaker 1: Democratic senators in the state of Nevada, for instance. You

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Speaker 1: still have two Democratic senators in the state of Michigan.

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Speaker 1: You're one and one in the state of Pennsylvania. So look,

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Speaker 1: at this point, I would favor the Democrats. You're not

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Speaker 1: going to get the state hasn't elected a Democratic senator

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Speaker 1: since two thousand and eight, so you got to give

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Speaker 1: Republicans a small advantage here. But I think it's very small.

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Speaker 1: Tillis made the race much tougher for Democrats now at

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Speaker 1: Tillis out of the way, So how do you get

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Speaker 1: the Democrats to three Senate seats? The three Republican seats

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Speaker 1: right now that look the most enticing to them. Number

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Speaker 1: one now is North Carolina with a bullet right right

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Speaker 1: up there, This becomes an open seat, seems like a

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Speaker 1: very plausible place for them to go find victory. Then

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Speaker 1: you have what's going on in Texas, where the Republicans

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Speaker 1: are likely to nominate the weakest general election candidate they

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Speaker 1: could find in Ken Paxton. He's a very polarizing figure.

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Speaker 1: He makes Ted krusing like a moderate. He's got all

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Speaker 1: sorts of character and ethics issues, And I don't know

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Speaker 1: if character matters anymore in American politics in Republican primaries.

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Speaker 1: I think that's been pre pointed out as John corn

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Speaker 1: And himself said he wanted to make this race up

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Speaker 1: and to see if character mattered still in politics. Well,

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Speaker 1: not in a Republican primary, it appears, And if Cornyan

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Speaker 1: does not seek there and Paxton is the candidate again,

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Speaker 1: I think you will have a I mean, that's a

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Speaker 1: very similar situation where you may have a free John

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Speaker 1: Cornyn voting, however, he feels like voting in ways that

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Speaker 1: sort of make Maga crazy but become pretty appealing to

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Speaker 1: swing voters and make it easy for Democrats to say, hey,

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Speaker 1: don't you want to have somebody who votes like John Cornyn?

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Speaker 2: Again?

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Speaker 1: All, of course, depending on who the Democrats nominate, right,

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Speaker 1: Colin Allread, perhaps this former astronaut who I find to be.

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Speaker 1: I think anybody that hasn't been in office before automatically

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Speaker 1: seems to be more of an appealing candidate than somebody

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Speaker 1: who's tried to run and failed. Just might I think

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Speaker 1: that's certainly if you're going to pick between who you

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Speaker 1: get to choose from, right better o' rourke, who's run before,

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Speaker 1: Colin Allred, who's run before a former astronaut? Right Like,

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Speaker 1: that's you could see the appeal on that. So but

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Speaker 1: either way, there's Texas in play. There's a poll out

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Speaker 1: earlier this week. Earlier last week, excuse me in Maine

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Speaker 1: had showed Susan Collins, who's up. Her overall favorable rating

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Speaker 1: was just in the toilet, right, she's got The problem

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Speaker 1: is she's not Maga, so Republicans don't like her and

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Speaker 1: she's too Republican for Democrats to like her anymore. Right,

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Speaker 1: there was a time where like Lisa Murkowski gets favorable

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Speaker 1: poll ratings from Democrats. Democrats in Alaska like her. So

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Speaker 1: while she maybe upside down with Maga, she's right side

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Speaker 1: up with essentially the rest of the electorate. Susan Collins

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Speaker 1: has figured out how to make everybody Matt kind of

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Speaker 1: like a journalist who isn't a progressive or isn't a

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Speaker 1: right winger, who somehow just sits there and you can

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Speaker 1: somehow piss off the left and the right simultaneously. I

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Speaker 1: think Susan Collins has pulled off that. Feet you throw

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Speaker 1: in the fact that she's been in office since the

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Speaker 1: twentieth century, she's been the United States Senate since the

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Speaker 1: last half of the twentieth century. I think that's the

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Speaker 1: you've been in office. I think you throw that, you

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Speaker 1: sprinkle a little bit at that ingredient into your race.

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Speaker 1: You've been in office again more. She got elected in

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Speaker 1: ninety six, I believe to that Senate. See, so she's

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Speaker 1: been there a very very very long time. So she

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Speaker 1: seems vulnerable, so you throw her in there. So now

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Speaker 1: you've got North Carolina Maine for sure. I'm not fully

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Speaker 1: on board Texas for the Democrats for what it's worth,

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Speaker 1: but it's their best shot to win a Senate see,

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Speaker 1: I think better than the shot better O'Rourke ended up

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Speaker 1: creating against Ted Cruise in twenty eighteen. That was one

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Speaker 1: of those where the result was closer than anybody expected,

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Speaker 1: but nobody bought it at the time. I think in

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Speaker 1: this case, this race feels already more competitive than we

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Speaker 1: thought that one would be, So that probably means more

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Speaker 1: money gets thrown in early et cetera. But then you

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Speaker 1: have a few other places where you have some mature races.

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Speaker 1: Jony Ernst does not look like a senator that I

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Speaker 1: told you this about a month ago, that I said,

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Speaker 1: I would bet that she's more likely not to seek

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Speaker 1: reelection than to go with the Senate race, just sort

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Speaker 1: of the way she's been behaving. And I have to

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Speaker 1: tell you I think the Tillis retirement the likely now

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Speaker 1: Cornyn retirement.

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Speaker 2: John Cornyn is all but hinted at this.

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Speaker 1: By the way, I wonder what this means for gocacity,

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Speaker 1: But I don't put Louisiana into the competitive category no

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Speaker 1: matter what happens there for what it's worth. I think

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Speaker 1: the state's just a bit too red. Maybe if John

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Speaker 1: Bell Edwards ran, but even then I'm skeptical. There asked

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Speaker 1: you see Larry Hogan in Maryland in twenty twenty four.

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Speaker 1: Popular governors who are ideologically on the wrong side of

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Speaker 1: a state usually struggle to do that. I think swing

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Speaker 1: state governors are different, which is why I think Cooper

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Speaker 1: has more than a boxer's chance in North Carolina. It's

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Speaker 1: much different if you're already sort of a decidedly either

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Speaker 1: red or blue state like that. But there's already three

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Speaker 1: Democrats jumping into that race, and they're all three pretty good.

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Speaker 1: At some point one of them two of them are

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Speaker 1: probably enough to drop out. No, there is no sort

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Speaker 1: of person that runs the Iowa Party these days, but

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Speaker 1: it does feel as if, but just the fact that

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Speaker 1: there are good candidates deciding they want to get in,

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Speaker 1: none of them seem to be super lefty. Obviously, if

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Speaker 1: the Democrats nominated somebody that was a bit more friendly

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Speaker 1: to you know, the ideology of Mamdani or even Bernie Sanders,

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Speaker 1: that might not be enough to win that state, could

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Speaker 1: get you a primary victory, right, and depending on how

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Speaker 1: you run as a populist, you know, are you a

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Speaker 1: democratic populist or a democratic socialist populist? Right, perhaps that's

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Speaker 1: going to be a new dividing line in primary politics.

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Speaker 1: But you throw Iowa in there, you throw Texas in there,

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Speaker 1: and that means, you know, they're just searching for one other. Right,

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Speaker 1: if you really feel pretty good and if the environment

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Speaker 1: goes your way, you're going to win North Carolina in Maine. Right,

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Speaker 1: these are swing states and they'll move in that direction.

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Speaker 1: So the question is where can they find where?

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Speaker 2: Where can they find a You have an open seat

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Speaker 2: in Alabama.

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Speaker 1: I don't believe it. I don't buy it. You might see,

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Speaker 1: you know, you keep hearing chatter Democrats are looking for

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Speaker 1: a candidate in Alaska. Mary Peltola, who was the at

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Speaker 1: large member of the House who just lost. She's sitting

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Speaker 1: out there. I think she would be a strong candidate.

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Speaker 1: I think Dan Sullivan. Look, he's not Lisa Murkowski, but

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Speaker 1: he's also somebody he's he's figured out how to be

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Speaker 1: soft on he's not a never trumper, but he sort

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Speaker 1: of has figured out how to vote Alaska first on

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Speaker 1: that front. So, and you know, it's been interesting. Sullivan

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Speaker 1: and Murkowski together have have made their votes necessary enough

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Speaker 1: that there's all sorts of goodies that Senate Republicans have

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Speaker 1: created to try to make sure they've kept their votes

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Speaker 1: in there. You know, if they again, that's what Democrats

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Speaker 1: have to do to pull up the Senate, They're going

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Speaker 1: to have to They've got the two obvious places in

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Speaker 1: North Carolina in Maine, they've gotta they've got to put

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Speaker 1: three or four other states in place so that they win.

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Speaker 1: All they need is one and obviously they got two

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Speaker 1: there you have it, right, but Alaska, And obviously there's

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Speaker 1: the real secret majority maker there is if Lisa Murkowski

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Speaker 1: decided to caucus with another one. There's the appointed senators

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Speaker 1: in Florida and Ohio. Right, you have Marco Rubio seat,

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Speaker 1: Jadie Vance's seat. Ashley Moody is the Republican appointee in

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Speaker 1: the Florida seat. Look, she has no name id. Yeah,

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Speaker 1: she's got a lot of work to do just to

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Speaker 1: introduce herself. And you may have a fairly competitive governor's race.

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Speaker 1: I'm more I'm more bullish on the governor's race for

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Speaker 1: Democrats than i am in the Senate race. There. But

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Speaker 1: the fact that it's an unknown candidate. Let's see, there's

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Speaker 1: not exactly a lot of Democrats are jumping jumping into

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Speaker 1: either one of those races. Then, of course you you

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Speaker 1: have the Ohio center race Shared Brown, Tim Ryan, the

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Speaker 1: last two Democratic nominees who ran better than expected in

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Speaker 1: those two center races back to back in Ohio, but

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Speaker 1: both lost. Right do they jump in? Does a Shared

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Speaker 1: Brown jump into John Houston again, a guy who's I

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Speaker 1: don't think has the name I d yet, the former

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Speaker 1: lieutenant governor now appointed US senator. But again, at this point,

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Speaker 1: you just want to put the seat in play, and

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Speaker 1: they might. They haven't gotten there in Kansas yet, doesn't

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Speaker 1: appear they're going to try. Democrats are going to try

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Speaker 1: to put Kentucky in play. Andy Basheer would be the

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Speaker 1: only reasonable Democrat they could recruit, and Andy Basheer has

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Speaker 1: got his eyes on twenty twenty eight and the presidency.

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Speaker 1: Mississippi is another state Democrats are searching for a candidate.

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Speaker 1: Sidney hed Smith only got fifty four percent the first time.

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Speaker 1: This is a state, you know. Mississippi is a state

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Speaker 1: that if Democrats put five years of voter registration work

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Speaker 1: into it, by year six, they could start possibly winning

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Speaker 1: races there. But the party doesn't ever consistently invest in Mississippi.

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Speaker 1: They only try to do it, you know, sort of

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Speaker 1: half in, half out. Nebraska. We know Dan Osborne is

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Speaker 1: likely to run as an independent that you know, would

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Speaker 1: we don't know what that could be. Pete Ricketts's is

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Speaker 1: running there. Maybe I'm more bullish on Democrats pulling off

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Speaker 1: Iowa than I am Nebraska. But Iowa, Nebraska, Kansas, I've

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Speaker 1: told you about these three states before. All of them

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Speaker 1: are getting hit hard by these aid cuts. All of

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Speaker 1: them are going to get hit hard by the Medicaid cuts.

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Speaker 1: So there's I think there's something there if they find

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Speaker 1: the candidates on that front, and then after that. I

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Speaker 1: don't buy Lindsey Graham this time. I don't think anybody's

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Speaker 1: going to fool themselves there at this point. And there's your,

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Speaker 1: there's your. That's the best they can hope for now.

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Speaker 1: Of course, Democrats are defending Michigan, they're having to defend Minnesota,

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Speaker 1: they have to defend Georgia. You know, if you're going

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Speaker 1: to win the Senate, they'd have to make sure they

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Speaker 1: don't lose any of those. And obviously I think George

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Speaker 1: is going to be the toughest one for them to hold.

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Speaker 1: But hey, guess what, They're struggling to unite around a candidate,

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Speaker 1: and the best candidate Republicans could have recruited, Brian Kemp,

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Speaker 1: chose not to run. So here's the bottom line this

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Speaker 1: Tom Tilli's retirement, especially if it's about I look Susan Collins.

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Speaker 1: John Cornyn is all but hinting at retirement. Susan Collins

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Speaker 1: has the pull numbers of somebody that shouldn't run again.

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Speaker 1: The fact of the matter is I was pretty skeptical.

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Speaker 1: You know, there's been all this. There's a lot of

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Speaker 1: people who waste a lot of time on substack talking

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Speaker 1: about these hypotheticals that somehow the Democrats may never win

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Speaker 1: the Senate ever again, or they're going to get locked

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Speaker 1: out ten years because there's this mindset that somehow, once

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Speaker 1: the state becomes a red state, you can't find candidates

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Speaker 1: to win it again. I will just tell you right now,

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Speaker 1: whenever I hear that crap, I tune it out, and

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Speaker 1: you should too. The fact is, you know, every two

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Speaker 1: years politics can change, especially in some of these states

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Speaker 1: that are very so you know nothing, you know, the

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Speaker 1: minute someone claims something with certainty in American politics, I

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Speaker 1: promise you that conventional wisdom will get upended. So look

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Speaker 1: a lot it didn't. Look it doesn't. It still is

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Speaker 1: a uphill battle for Democrats to win the Senate in

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Speaker 1: twenty twenty six.

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Speaker 2: But here's the reality. They're in the game there.

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Speaker 1: Basically, it's like the Indiana Pacers in Oklahoma City. You

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Speaker 1: look on papers, shouldn't have been close. But at the

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Speaker 1: end of the day, this is, at a minimum, is

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Speaker 1: going to be something that we're not sure about going

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Speaker 1: into election day twenty twenty six. And the fact that

430
00:23:54,520 --> 00:23:56,080
Speaker 1: that's where we are more than a year and a

431
00:23:56,119 --> 00:23:59,240
Speaker 1: half before November of twenty twenty six, I think shows

432
00:23:59,280 --> 00:24:03,800
Speaker 1: you all read the struggles that the Republicans nationally are

433
00:24:03,840 --> 00:24:08,040
Speaker 1: having to defend Trump's agenda. And again, this bill is

434
00:24:08,119 --> 00:24:11,880
Speaker 1: already setting up to be I mean, Tillis has chosen

435
00:24:12,040 --> 00:24:14,760
Speaker 1: not to run for reelection because he can't sell this

436
00:24:14,800 --> 00:24:18,879
Speaker 1: bill in North Carolina. That is everything you need to

437
00:24:18,920 --> 00:24:22,480
Speaker 1: know right now about the state of the Trump agenda

438
00:24:22,920 --> 00:24:26,520
Speaker 1: and public opinion in American politics at the moment. So

439
00:24:26,560 --> 00:24:28,800
Speaker 1: we've had a week that's really shaken up. I think

440
00:24:28,840 --> 00:24:31,600
Speaker 1: the American political landscape. It started on Tuesday in New

441
00:24:31,680 --> 00:24:34,919
Speaker 1: York City with the upset win of z On Mamdani,

442
00:24:35,280 --> 00:24:37,679
Speaker 1: and now you have an entire political party on the

443
00:24:37,680 --> 00:24:41,360
Speaker 1: Democratic side really ringing its hands over democratic socialism. And

444
00:24:41,600 --> 00:24:44,200
Speaker 1: a quote that Mamdani gave to meet the press saying

445
00:24:44,280 --> 00:24:47,159
Speaker 1: he didn't think there should be any billionaires is only

446
00:24:47,200 --> 00:24:49,639
Speaker 1: going to stir the pot more, only likely to divide

447
00:24:49,640 --> 00:24:54,080
Speaker 1: the Democratic Party more. And then of course you have

448
00:24:54,119 --> 00:24:56,680
Speaker 1: what Donald Trump is doing by purging the Republican Party

449
00:24:56,720 --> 00:25:00,960
Speaker 1: of anybody that at all challenges the King. Right, if

450
00:25:00,960 --> 00:25:04,520
Speaker 1: you question the King, you're out right asked Tom Massey,

451
00:25:05,119 --> 00:25:07,960
Speaker 1: asked Tom tillis apparently anybody with the first name of

452
00:25:08,000 --> 00:25:12,440
Speaker 1: Tom half kidding. But the point is is that this

453
00:25:12,760 --> 00:25:17,000
Speaker 1: is not an easy time to be somebody who sort

454
00:25:17,000 --> 00:25:22,120
Speaker 1: of caught in between, if you will. And it sort

455
00:25:22,119 --> 00:25:24,040
Speaker 1: of sets up an interesting situation when you sort of

456
00:25:24,040 --> 00:25:28,000
Speaker 1: look at this, how the Republican Party is putting the

457
00:25:28,040 --> 00:25:30,439
Speaker 1: other this bill, and how sort of loyalty to Trump

458
00:25:30,480 --> 00:25:33,639
Speaker 1: is essentially the only unifying factor that is going to

459
00:25:33,640 --> 00:25:36,080
Speaker 1: get this bill across the finish line, which is you

460
00:25:36,200 --> 00:25:38,639
Speaker 1: have to show loyalty to Trump if you don't the

461
00:25:38,680 --> 00:25:43,480
Speaker 1: bill dies and your political career dies as well, And

462
00:25:43,560 --> 00:25:46,800
Speaker 1: all of it is sort of triggered a lot of

463
00:25:47,000 --> 00:25:49,440
Speaker 1: hand ringing, right, You've had the Supreme Court rulings triggered

464
00:25:49,440 --> 00:25:52,639
Speaker 1: more hand ringing about are all the guardrails starting to fail?

465
00:25:53,119 --> 00:25:55,480
Speaker 1: My friends at Axios, Mike Calen and Jim Vandehia a

466
00:25:55,560 --> 00:25:59,359
Speaker 1: very provocative column at the end of last week that

467
00:25:59,440 --> 00:26:01,440
Speaker 1: had to do with all the new precedents that Donald

468
00:26:01,440 --> 00:26:05,359
Speaker 1: Trump is set with the presidency and that and what

469
00:26:05,440 --> 00:26:09,720
Speaker 1: they were implying is that one day these precedents that

470
00:26:09,880 --> 00:26:13,440
Speaker 1: conservatives are going to regret having a Republican president set

471
00:26:13,480 --> 00:26:16,520
Speaker 1: these new precedents if a progressive president comes in and

472
00:26:16,640 --> 00:26:20,040
Speaker 1: essentially borrows the playbook of the of the of Donald

473
00:26:20,040 --> 00:26:24,000
Speaker 1: Trump and runs rough shot over the Constitution, but not

474
00:26:24,440 --> 00:26:27,320
Speaker 1: for the for the for the benefit of the right,

475
00:26:27,400 --> 00:26:30,320
Speaker 1: but in this time, for the benefit of the left.

476
00:26:31,280 --> 00:26:34,480
Speaker 1: And I think that that's the thing that concerns me

477
00:26:34,880 --> 00:26:37,960
Speaker 1: as much as anything that's out there these days. You know,

478
00:26:38,760 --> 00:26:40,840
Speaker 1: the word unprecedented. We talk about it all the time.

479
00:26:40,960 --> 00:26:44,000
Speaker 1: Everything's unprecedented. It's the most overused word in the Trump era.

480
00:26:44,119 --> 00:26:46,639
Speaker 1: Five syllable crutch. We've leaned on every time Donald Trump

481
00:26:46,840 --> 00:26:49,919
Speaker 1: tramples another political norm. For a president to do this,

482
00:26:50,000 --> 00:26:52,600
Speaker 1: it's unprecedented for the courts to even have to consider this.

483
00:26:52,680 --> 00:26:55,600
Speaker 1: It's unprecedented. And yet here we are nearly a decade

484
00:26:55,640 --> 00:26:58,840
Speaker 1: into his political dominance, and what was once seen unthinkable

485
00:26:58,920 --> 00:27:02,520
Speaker 1: is now almost expected. Trump has tested the boundaries of

486
00:27:02,560 --> 00:27:05,879
Speaker 1: presidential power more aggressively, more frequently than any president in

487
00:27:05,920 --> 00:27:09,680
Speaker 1: modern history. Yes, Roosevelt and Lincoln pushed the limits of

488
00:27:09,720 --> 00:27:13,399
Speaker 1: their powers, but they did so for a reason. Wartime

489
00:27:14,000 --> 00:27:16,560
Speaker 1: there was sort of life and death decisions they were making,

490
00:27:17,040 --> 00:27:19,160
Speaker 1: and so they were making some of these disservice they

491
00:27:19,240 --> 00:27:23,360
Speaker 1: decisions believe what they believed was on national survival. Trump's

492
00:27:23,359 --> 00:27:26,400
Speaker 1: motivations to test the boundaries of his power, more often

493
00:27:26,440 --> 00:27:30,000
Speaker 1: than not, they're personal, avoiding criminal exposure for him more's

494
00:27:30,040 --> 00:27:33,840
Speaker 1: friends and riching his family, or settling political scores. Now,

495
00:27:33,840 --> 00:27:35,600
Speaker 1: he's not the first president to push it like this,

496
00:27:36,800 --> 00:27:38,480
Speaker 1: but he is the first to do it just about

497
00:27:38,480 --> 00:27:41,639
Speaker 1: every day, with no pretense of ever serving a broader

498
00:27:41,680 --> 00:27:44,520
Speaker 1: constitutional or national interest. And because of that, he has

499
00:27:44,560 --> 00:27:47,840
Speaker 1: set a precedent that's dangerously easy for others to follow.

500
00:27:49,600 --> 00:27:53,639
Speaker 1: And you know, it is it is really you know,

501
00:27:54,560 --> 00:27:57,680
Speaker 1: many of the justifications, of course, for Trump's behavior come

502
00:27:57,720 --> 00:28:02,119
Speaker 1: from these imagined slight by past democratic presidents. Right, a

503
00:28:02,160 --> 00:28:05,600
Speaker 1: false equivalence. Bilk on what about is Biden and Obama

504
00:28:05,800 --> 00:28:09,679
Speaker 1: supposedly did you know incrementally something similar to what Trump

505
00:28:09,760 --> 00:28:13,679
Speaker 1: is proposed to do? But he does it. But what

506
00:28:13,720 --> 00:28:17,080
Speaker 1: Trump do does it's on steroids. Right If you look closely,

507
00:28:17,119 --> 00:28:20,800
Speaker 1: take Hunter Biden as an example, right, it becomes yes,

508
00:28:20,880 --> 00:28:23,360
Speaker 1: Hunter Biden decided to get rich off his father's last

509
00:28:23,440 --> 00:28:26,399
Speaker 1: name and tried to get do business around the world

510
00:28:26,640 --> 00:28:30,320
Speaker 1: using his father's last name in influence. Right, what Hunter

511
00:28:30,359 --> 00:28:33,320
Speaker 1: did was wrong. But the Trump kids, they're taking the

512
00:28:33,400 --> 00:28:35,800
Speaker 1: hundred playbook and it's times a thousand. They're doing it

513
00:28:35,840 --> 00:28:38,480
Speaker 1: on steroids. They use their office, their father's office, to

514
00:28:38,480 --> 00:28:43,400
Speaker 1: make money, ink foreign deals, launch vanity businesses. It's not

515
00:28:43,480 --> 00:28:45,760
Speaker 1: just unethical. Let's praise it. And of course, again with

516
00:28:45,800 --> 00:28:47,479
Speaker 1: the Speaker of the House said, the only difference is

517
00:28:47,720 --> 00:28:50,160
Speaker 1: that Trump tells you that he's doing it in advance. Again,

518
00:28:50,640 --> 00:28:53,280
Speaker 1: looking at the camera as you're shoplifting and saying and

519
00:28:53,360 --> 00:28:56,560
Speaker 1: waving at the camera and saying thank you. The silence

520
00:28:56,560 --> 00:28:58,880
Speaker 1: for most Republicans is telling, and look what happens if

521
00:28:58,880 --> 00:29:02,640
Speaker 1: you do speak out, might become a Tom Tillis. Some

522
00:29:02,680 --> 00:29:04,400
Speaker 1: of them know it, some of them are too scared

523
00:29:04,480 --> 00:29:07,080
Speaker 1: or compromised to partisan to speak up. Then there's a

524
00:29:07,080 --> 00:29:09,240
Speaker 1: guy like Mike Lee. He was once a voice for

525
00:29:09,320 --> 00:29:12,520
Speaker 1: constitutional conservatism. Now he's been reduced to a troll level

526
00:29:12,800 --> 00:29:16,280
Speaker 1: trigger outrage with no moral compass guiding him at all.

527
00:29:16,840 --> 00:29:18,840
Speaker 1: I don't know what happened to that guy. This is

528
00:29:18,880 --> 00:29:21,360
Speaker 1: the constitutional crisis no one wants to name that we're

529
00:29:21,400 --> 00:29:24,640
Speaker 1: in right now. We've grown numb to power being wielded

530
00:29:24,640 --> 00:29:27,480
Speaker 1: for personal and partisan game. Take what happened at the

531
00:29:27,560 --> 00:29:31,840
Speaker 1: University of Virginia. Just bullying the University of Virginia to

532
00:29:31,880 --> 00:29:35,320
Speaker 1: fire its president because somebody probably at the just Department

533
00:29:35,400 --> 00:29:37,960
Speaker 1: is a uvlum and thought, Hey, I'm going to take

534
00:29:37,960 --> 00:29:40,880
Speaker 1: advantage of this moment of anti wokeness and I'm going

535
00:29:40,920 --> 00:29:43,360
Speaker 1: to get my way at my school. So it gets

536
00:29:43,440 --> 00:29:44,120
Speaker 1: cherry picked.

537
00:29:44,520 --> 00:29:44,720
Speaker 2: Right.

538
00:29:44,760 --> 00:29:48,160
Speaker 1: We have no we have no effort at all to

539
00:29:48,240 --> 00:29:52,520
Speaker 1: at least show some justification here. What's being done was

540
00:29:52,560 --> 00:29:56,600
Speaker 1: just blatantly unconstitutional, but it's going to happen because the

541
00:29:56,600 --> 00:29:58,640
Speaker 1: school doesn't want to deal with the funds doesn't want

542
00:29:58,640 --> 00:30:02,240
Speaker 1: to deal with lawsuits, which is understandable in some ways.

543
00:30:02,240 --> 00:30:05,400
Speaker 1: But here's here's what's really frustrating. Much of the public

544
00:30:05,440 --> 00:30:08,600
Speaker 1: doesn't seem to care that this behavior is becoming normal.

545
00:30:09,080 --> 00:30:11,240
Speaker 1: We've been part of it. Sadly is I think most

546
00:30:11,280 --> 00:30:13,800
Speaker 1: people believe all politics has always been this way, that

547
00:30:13,840 --> 00:30:16,960
Speaker 1: Trump didn't break the system, he just exposed it. But

548
00:30:17,000 --> 00:30:21,000
Speaker 1: that is not true. There was a genuine attempt post

549
00:30:21,080 --> 00:30:25,000
Speaker 1: Watergate to building more ethical government. We put in all

550
00:30:25,040 --> 00:30:28,520
Speaker 1: sorts of transparency laws. Inspector generals were added all over

551
00:30:28,560 --> 00:30:31,840
Speaker 1: the place. Campaign finance reforms were implemented for the first time.

552
00:30:32,400 --> 00:30:36,240
Speaker 1: It wasn't perfect, but we were making progress. The corruption

553
00:30:36,400 --> 00:30:38,960
Speaker 1: that Donald Trump learned politics about in New York City

554
00:30:38,960 --> 00:30:42,120
Speaker 1: in the fifties, sixties, and seventies is not what it

555
00:30:42,200 --> 00:30:45,920
Speaker 1: is today. And yet Donald Trump's mind, all politics that

556
00:30:46,040 --> 00:30:48,280
Speaker 1: was the way politics was conducted in the sixties is

557
00:30:48,280 --> 00:30:50,760
Speaker 1: the way it was conducted today. Everything is paid to play,

558
00:30:51,040 --> 00:30:53,840
Speaker 1: pure and simple, and Donald Trump thinks, great, now I'm

559
00:30:53,840 --> 00:30:56,560
Speaker 1: the guy you pay in order to play, and that's

560
00:30:56,600 --> 00:30:58,959
Speaker 1: all he cares about. He thinks that's how it works.

561
00:30:59,480 --> 00:31:02,160
Speaker 1: And everybody has joined with them and this is what

562
00:31:02,200 --> 00:31:05,040
Speaker 1: we're stuck at. And my biggest fear is that the

563
00:31:05,080 --> 00:31:07,880
Speaker 1: Democrat that some on the left are going to look

564
00:31:08,080 --> 00:31:11,520
Speaker 1: at the success of Trump pulling this off and not

565
00:31:11,680 --> 00:31:16,440
Speaker 1: see it as a national emergency, but instead see it

566
00:31:16,440 --> 00:31:20,440
Speaker 1: as a playbook. And this is the question already playing

567
00:31:20,480 --> 00:31:23,240
Speaker 1: out in democratic primaries. What does the what is the

568
00:31:23,360 --> 00:31:25,320
Speaker 1: right answer to confronting Trump?

569
00:31:25,360 --> 00:31:26,360
Speaker 2: And Trump isn't.

570
00:31:27,600 --> 00:31:30,400
Speaker 1: Do Democrats are having this debate? Do they nominate a

571
00:31:30,440 --> 00:31:34,240
Speaker 1: steady hand of institutionalists or do they get the firebrand

572
00:31:34,320 --> 00:31:38,479
Speaker 1: energy of transformational progressives like mister mom donnie. Do they

573
00:31:38,520 --> 00:31:41,320
Speaker 1: play the Trump game? Or do they rewrite the rules.

574
00:31:42,160 --> 00:31:44,080
Speaker 1: I'll tell you this, here's a question that I would

575
00:31:44,120 --> 00:31:46,120
Speaker 1: like to see some pollsters ask. I think there's sort

576
00:31:46,120 --> 00:31:48,360
Speaker 1: of there's too many times we ask only two choices,

577
00:31:48,400 --> 00:31:50,200
Speaker 1: you know, sort of do you want this, you know,

578
00:31:50,240 --> 00:31:54,160
Speaker 1: this Trump version of change in America or progressive vision?

579
00:31:54,600 --> 00:31:56,480
Speaker 1: I think you got to ask how many people want

580
00:31:56,560 --> 00:32:00,680
Speaker 1: incrementalism slash status quo meaning let's, you know, things are

581
00:32:00,840 --> 00:32:03,320
Speaker 1: things continue to get a little bit better, let's not

582
00:32:03,480 --> 00:32:05,240
Speaker 1: upset the apple cart, right. I don't know how you

583
00:32:05,280 --> 00:32:08,160
Speaker 1: measure that, but I think it's sort of three choices

584
00:32:08,200 --> 00:32:11,520
Speaker 1: here that the public is actually debating, and yet we

585
00:32:11,560 --> 00:32:16,400
Speaker 1: only present two bright lines when one is representative about

586
00:32:16,440 --> 00:32:19,200
Speaker 1: six to ten percent of the Democratic Party and one

587
00:32:19,240 --> 00:32:21,600
Speaker 1: is representative of maybe ten to fifteen percent of the

588
00:32:21,600 --> 00:32:26,640
Speaker 1: Republican Party. And yet it is pure dominance on that front.

589
00:32:27,440 --> 00:32:29,080
Speaker 1: And I think that's going to be a real question.

590
00:32:30,360 --> 00:32:31,479
Speaker 2: What does you know?

591
00:32:31,600 --> 00:32:36,560
Speaker 1: It is tough to sell, you know, after the Nixon debacle,

592
00:32:37,880 --> 00:32:40,240
Speaker 1: the Democrats nominated a guy like Jimmy Carter because he

593
00:32:40,320 --> 00:32:41,960
Speaker 1: was One of the things he said is I'll never

594
00:32:41,960 --> 00:32:44,640
Speaker 1: tell a lie, and it was one of the it

595
00:32:44,680 --> 00:32:46,840
Speaker 1: was an important message. The point is it was like, hey,

596
00:32:46,960 --> 00:32:50,480
Speaker 1: let's let's nominate a Sunday school teacher after Richard Nixon.

597
00:32:50,520 --> 00:32:52,440
Speaker 1: It's what the country wanted. And literally they got a

598
00:32:52,440 --> 00:32:54,320
Speaker 1: Sunday school teacher. Now, it turned out he was a

599
00:32:54,400 --> 00:32:57,840
Speaker 1: terrible manager. He was a micromanager and that didn't work out.

600
00:32:57,960 --> 00:33:02,120
Speaker 1: You know, it was what it was. But the reaction

601
00:33:02,240 --> 00:33:05,080
Speaker 1: of the public, right, they wanted clean as a whistle.

602
00:33:06,000 --> 00:33:08,080
Speaker 2: What is the public going to want this con post Trump?

603
00:33:08,600 --> 00:33:10,760
Speaker 1: Are they going to want to prevent the opportunity of

604
00:33:10,800 --> 00:33:14,320
Speaker 1: another Trump again so that he doesn't have these monarchical

605
00:33:14,560 --> 00:33:17,080
Speaker 1: like tendencies where they just pick and choose. No, you

606
00:33:17,120 --> 00:33:19,680
Speaker 1: don't get to be a university president anymore. No, we're

607
00:33:19,680 --> 00:33:22,960
Speaker 1: going to just defund New York City because we don't

608
00:33:23,040 --> 00:33:26,080
Speaker 1: like the choice you made in your locally controlled government.

609
00:33:26,800 --> 00:33:29,560
Speaker 1: We're going to fire prosecutors because we don't like that

610
00:33:30,000 --> 00:33:31,200
Speaker 1: duly elected prosecutor.

611
00:33:31,200 --> 00:33:32,640
Speaker 2: I'm talking about the state of Florida we're around.

612
00:33:32,640 --> 00:33:39,600
Speaker 1: De Santis is practiced this type of pugilistic politics, unconstitutional politics. Arguably,

613
00:33:39,920 --> 00:33:44,280
Speaker 1: it was exactly what the Founders were fighting. And I

614
00:33:44,400 --> 00:33:46,040
Speaker 1: know there's going to be plenty on the left. They're

615
00:33:46,040 --> 00:33:47,400
Speaker 1: going to be tempting to say, Hey, if you can't

616
00:33:47,400 --> 00:33:49,680
Speaker 1: beat them, join them. And they're going to argue that

617
00:33:49,720 --> 00:33:53,160
Speaker 1: the public doesn't care about the ethics stuff, the public

618
00:33:53,200 --> 00:33:56,400
Speaker 1: doesn't care enough about character. Don't get caught going down

619
00:33:56,400 --> 00:33:58,840
Speaker 1: that road. You're going to have to instead fight fire

620
00:33:58,880 --> 00:34:03,920
Speaker 1: with fire. All I'll warnt is when you go down

621
00:34:03,960 --> 00:34:07,080
Speaker 1: that road, do we really want if we don't like

622
00:34:07,160 --> 00:34:10,600
Speaker 1: that the constitutional guardrails are getting weakened by the hour

623
00:34:11,200 --> 00:34:15,680
Speaker 1: by a scared Supreme Corps, by a scared legislative branch.

624
00:34:18,120 --> 00:34:22,320
Speaker 1: Is the answer really to just exploit that, exploit that fear,

625
00:34:22,360 --> 00:34:25,600
Speaker 1: but do it from the left, or should be or

626
00:34:25,640 --> 00:34:29,959
Speaker 1: should the goal be to firm up these institutions, firm

627
00:34:30,040 --> 00:34:34,000
Speaker 1: up the guard constitutional guardrails, so that maybe we prevent

628
00:34:35,200 --> 00:34:39,839
Speaker 1: another demagogue from exploiting the system again. On one hand,

629
00:34:39,880 --> 00:34:42,040
Speaker 1: the answer seems easy, and we know what most of

630
00:34:42,120 --> 00:34:44,600
Speaker 1: us would pick, what we would prefer to work for,

631
00:34:45,040 --> 00:34:47,160
Speaker 1: or who we would work with if this were a

632
00:34:47,280 --> 00:34:50,840
Speaker 1: job interview. And yet I think we all know what

633
00:34:50,880 --> 00:34:54,000
Speaker 1: the public is most likely to respond to. And in fact,

634
00:34:54,120 --> 00:34:56,960
Speaker 1: that's actually the most fascinating part of my conversation with

635
00:34:57,040 --> 00:35:00,520
Speaker 1: Kristen Sultas Anderson. She's a Republican polster to have on,

636
00:35:00,640 --> 00:35:06,120
Speaker 1: but she is She's somebody that is probably understands the

637
00:35:06,120 --> 00:35:09,080
Speaker 1: the shift in our in our zeitgeist. I don't know

638
00:35:09,120 --> 00:35:11,360
Speaker 1: how else to call it, and I know zeitgeist is

639
00:35:11,400 --> 00:35:14,160
Speaker 1: an overused word, but I lean on it because it's

640
00:35:14,160 --> 00:35:18,440
Speaker 1: sort of it's it's message culture sort of wrapped up

641
00:35:18,480 --> 00:35:21,759
Speaker 1: in one. And she posits in this conversation, I want

642
00:35:21,800 --> 00:35:23,480
Speaker 1: you to take look and I'd love to hear your

643
00:35:23,480 --> 00:35:27,200
Speaker 1: feedback on this that you know she sees Mom Donnie

644
00:35:27,239 --> 00:35:30,120
Speaker 1: almost as an extension of Trump right, which is if

645
00:35:30,160 --> 00:35:33,279
Speaker 1: you can dominate her. Thing is is the theory of

646
00:35:33,320 --> 00:35:37,399
Speaker 1: American politics now the following. If you can dominate the conversation,

647
00:35:37,560 --> 00:35:41,160
Speaker 1: it doesn't matter what you stand for, You're going to win. Right.

648
00:35:41,239 --> 00:35:44,680
Speaker 1: You can have unpopular beliefs, But if you're dominating the conversation,

649
00:35:44,800 --> 00:35:48,560
Speaker 1: if you're dominating the attention, if you will of that

650
00:35:48,640 --> 00:35:51,640
Speaker 1: campaign you're and you have the per and you have

651
00:35:51,680 --> 00:35:56,160
Speaker 1: a compelling personality, you can overcome unpopular ideas. Donald Trump's

652
00:35:56,160 --> 00:35:59,000
Speaker 1: pulled it off because we see as you know, in practice,

653
00:35:59,200 --> 00:36:02,200
Speaker 1: you know he he's a more popular.

654
00:36:01,800 --> 00:36:03,800
Speaker 2: Candidate than he is when he's in office.

655
00:36:03,920 --> 00:36:06,880
Speaker 1: Right, all of his ideas pull well, and when he

656
00:36:06,880 --> 00:36:11,440
Speaker 1: starts implementing they all pour polling. Is is that the

657
00:36:11,560 --> 00:36:14,279
Speaker 1: new way you've got to practice politics? Can you not

658
00:36:14,480 --> 00:36:18,640
Speaker 1: be a technocrat like Michael Bloomberg? Right, Andy Cuomo, I

659
00:36:18,680 --> 00:36:20,840
Speaker 1: don't want to say he was a flawed candidate for

660
00:36:20,880 --> 00:36:23,319
Speaker 1: a variety of reasons, but he also was kind of

661
00:36:24,480 --> 00:36:28,360
Speaker 1: bragging about his ability to be a technocrat. So it

662
00:36:28,600 --> 00:36:33,839
Speaker 1: is that just now out of being his competence no

663
00:36:33,920 --> 00:36:38,160
Speaker 1: longer a characteristic voters will reward at the ballot box.

664
00:36:38,880 --> 00:36:42,839
Speaker 1: They miss it when it's not there, and they regret it, right,

665
00:36:43,520 --> 00:36:44,960
Speaker 1: but do they actually vote for it?

666
00:36:45,040 --> 00:36:45,160
Speaker 3: Right?

667
00:36:45,160 --> 00:36:46,480
Speaker 1: It's like the issue, it's like what I've told you

668
00:36:46,480 --> 00:36:49,399
Speaker 1: point the issue of campaign financial reform when we see

669
00:36:49,400 --> 00:36:51,600
Speaker 1: it in practice and how easy it is for pay

670
00:36:51,640 --> 00:36:55,640
Speaker 1: to play to work for various industries, various players. We wonder,

671
00:36:55,640 --> 00:36:58,440
Speaker 1: how come there's not any laws against this? And then

672
00:36:58,480 --> 00:37:01,640
Speaker 1: when candidates campaign on these issues, Oh, you're not talking

673
00:37:01,640 --> 00:37:06,919
Speaker 1: about the issues I care about. So unless somebody gets

674
00:37:06,960 --> 00:37:11,680
Speaker 1: better at connecting these dots for the public, I don't

675
00:37:11,719 --> 00:37:14,680
Speaker 1: know how we get these issues sort of at the forefront.

676
00:37:14,719 --> 00:37:20,040
Speaker 1: But hey, if being able to grab the attention is

677
00:37:20,080 --> 00:37:23,160
Speaker 1: the best way to win over a political electorate, well

678
00:37:23,160 --> 00:37:28,880
Speaker 1: maybe there's some incredible charismatic person who will make guardrails.

679
00:37:28,120 --> 00:37:29,720
Speaker 2: And the constitution great again.

680
00:37:30,600 --> 00:37:33,480
Speaker 1: And with that, enjoy your conversation, my conversation with Kristin

681
00:37:33,520 --> 00:37:48,240
Speaker 1: Sultan Satterson. Well, joining me now is Kristin Sultice Anderson

682
00:37:48,280 --> 00:37:50,359
Speaker 1: echelon Insights, right, Kristin, do I have that right?

683
00:37:50,520 --> 00:37:51,160
Speaker 2: That's correct?

684
00:37:51,640 --> 00:37:55,360
Speaker 1: That is I've known her. I want to say, fifteen years,

685
00:37:55,400 --> 00:37:58,759
Speaker 1: you twenty years. Maybe now you got your start with

686
00:37:58,800 --> 00:38:01,320
Speaker 1: an old friend of mine named Dave Winston. David Winston

687
00:38:01,680 --> 00:38:06,399
Speaker 1: a longtime Republican polster. David Winston and I you may

688
00:38:06,480 --> 00:38:11,520
Speaker 1: now know this only by story. We were the first

689
00:38:11,600 --> 00:38:13,320
Speaker 1: people to put polling on the internet.

690
00:38:13,920 --> 00:38:14,040
Speaker 2: MM.

691
00:38:14,920 --> 00:38:18,000
Speaker 1: There was no real Cleare politics, There was no Nate Silver.

692
00:38:18,560 --> 00:38:20,719
Speaker 1: There was me and David Winston politics.

693
00:38:20,719 --> 00:38:21,279
Speaker 2: Now, so.

694
00:38:23,000 --> 00:38:25,800
Speaker 1: You come from good You come from a good lineage

695
00:38:25,960 --> 00:38:28,600
Speaker 1: of good people on that front.

696
00:38:28,600 --> 00:38:30,680
Speaker 2: One of the smart well, you know, David used to

697
00:38:30,719 --> 00:38:31,080
Speaker 2: tell me.

698
00:38:31,760 --> 00:38:35,000
Speaker 3: David used to tell me that you all would occasionally

699
00:38:35,040 --> 00:38:39,480
Speaker 3: get emails from a young student at the University of

700
00:38:39,480 --> 00:38:43,560
Speaker 3: Pennsylvania named Patrick Gruffini who was really interested in politics.

701
00:38:43,640 --> 00:38:45,520
Speaker 3: And so he has now been my business partner for

702
00:38:45,560 --> 00:38:48,680
Speaker 3: the last eleven years. So it really all has come

703
00:38:48,719 --> 00:38:49,320
Speaker 3: full circle.

704
00:38:49,719 --> 00:38:53,480
Speaker 1: Well, and you bring up I love I love Patrick substack.

705
00:38:53,920 --> 00:38:55,920
Speaker 1: I tell him that I think it's a terrific that

706
00:38:56,000 --> 00:38:58,440
Speaker 1: weekly especially he was doing that weekly newsletter for a

707
00:38:58,480 --> 00:39:00,160
Speaker 1: while and I know now he's turned in more into

708
00:39:00,160 --> 00:39:03,279
Speaker 1: a substack where you know, it's sort of like, hey,

709
00:39:03,560 --> 00:39:05,200
Speaker 1: check out what I found this week. This is an

710
00:39:05,200 --> 00:39:08,040
Speaker 1: interesting piece of data, which is why I'm excited to

711
00:39:08,040 --> 00:39:10,600
Speaker 1: have you on. We are taping. I want to timestamp

712
00:39:10,680 --> 00:39:11,920
Speaker 1: this a little bit. We're taping at the end of

713
00:39:12,000 --> 00:39:15,920
Speaker 1: June June twenty on a Friday, June twenty seventh, and

714
00:39:17,560 --> 00:39:21,719
Speaker 1: we just got it was Christmas for Stata geeks this

715
00:39:21,800 --> 00:39:26,640
Speaker 1: week because Pew came out with its how describe what

716
00:39:26,760 --> 00:39:32,160
Speaker 1: Pugh did? They call it a voter validation survey of sorts,

717
00:39:32,160 --> 00:39:34,200
Speaker 1: But what it really is is the it sort of

718
00:39:34,640 --> 00:39:36,680
Speaker 1: the it takes an exit poll and makes it more

719
00:39:36,719 --> 00:39:38,840
Speaker 1: accurate is probably the quick way I'd explain it.

720
00:39:38,840 --> 00:39:39,879
Speaker 2: But how would you explain it?

721
00:39:40,880 --> 00:39:46,440
Speaker 3: Yeah, A voter validation process basically says, you know, you

722
00:39:46,480 --> 00:39:49,000
Speaker 3: can do a survey where you're talking to folks who

723
00:39:49,040 --> 00:39:53,000
Speaker 3: are registered voters. They are people who exist on the

724
00:39:53,080 --> 00:39:56,440
Speaker 3: voter file, but that's not necessarily the same as people

725
00:39:56,560 --> 00:40:00,319
Speaker 3: who actually voted. So the great thing about the voter

726
00:40:00,400 --> 00:40:03,959
Speaker 3: file is after an election, it tells you who turned out,

727
00:40:04,800 --> 00:40:07,320
Speaker 3: and so you can go back and see of somebody

728
00:40:07,360 --> 00:40:10,600
Speaker 3: who said, yes, I turned out in the twenty twenty

729
00:40:10,600 --> 00:40:14,319
Speaker 3: four election. We now can know if that's true or not.

730
00:40:15,239 --> 00:40:18,880
Speaker 3: In Pew's case, I believe they used a couple different vendors.

731
00:40:19,239 --> 00:40:21,120
Speaker 3: I don't think they named them. But if you work

732
00:40:21,120 --> 00:40:22,880
Speaker 3: in this space, you can kind of read between the

733
00:40:22,920 --> 00:40:26,400
Speaker 3: lines and guessing one is either data trust or I

734
00:40:26,440 --> 00:40:28,600
Speaker 3: three sixty because those are the They said, one vendor

735
00:40:28,640 --> 00:40:32,040
Speaker 3: worked with conservatives, one vendor works with progressives, So like

736
00:40:32,080 --> 00:40:34,440
Speaker 3: I said, Catalyt, you know, I'm less familiar with the

737
00:40:34,480 --> 00:40:37,200
Speaker 3: ecosystem on that side. And then one is nonpartisan, which

738
00:40:37,239 --> 00:40:39,640
Speaker 3: I'm assuming is L two. We use L two a

739
00:40:39,680 --> 00:40:41,640
Speaker 3: lot at my company. So anyhow, I'm like, it's funny

740
00:40:41,800 --> 00:40:43,279
Speaker 3: going through and trying to figure out where they got

741
00:40:43,320 --> 00:40:45,680
Speaker 3: the lists. Anyhow, the point is they go through and

742
00:40:45,719 --> 00:40:48,520
Speaker 3: they figure out not just people who claim they voted,

743
00:40:48,760 --> 00:40:51,120
Speaker 3: but people where there is proof that you actually voted

744
00:40:51,120 --> 00:40:54,239
Speaker 3: in twenty twenty four and that can give you.

745
00:40:55,960 --> 00:40:58,480
Speaker 1: To their old data. Right, Like, they basically go back,

746
00:40:58,520 --> 00:41:02,200
Speaker 1: these are interviews they can throughout the twenty twenty four campaign.

747
00:41:02,800 --> 00:41:05,279
Speaker 1: Then they actually said, okay, these people call themselves likely

748
00:41:05,360 --> 00:41:07,920
Speaker 1: voters and and you know what I love about it

749
00:41:07,960 --> 00:41:10,520
Speaker 1: is that it gives you both a clear picture of

750
00:41:11,680 --> 00:41:18,520
Speaker 1: who voted. But it also is the single best a

751
00:41:18,680 --> 00:41:22,040
Speaker 1: survey that we get of non voters and understanding what

752
00:41:22,120 --> 00:41:24,160
Speaker 1: is the makeup of the people who did not vote,

753
00:41:24,440 --> 00:41:27,360
Speaker 1: because you know, obviously if you figure out how to

754
00:41:27,360 --> 00:41:29,400
Speaker 1: get some of them to vote, you can change an electorate.

755
00:41:29,440 --> 00:41:33,160
Speaker 1: But it frustrates me to all end. I have this fight.

756
00:41:33,200 --> 00:41:34,680
Speaker 1: I used to have this fight with my own pollsters.

757
00:41:35,200 --> 00:41:37,680
Speaker 1: I love. I want to spend more time understanding the

758
00:41:37,760 --> 00:41:41,160
Speaker 1: non voter. I think sometimes we don't fully fully appreciate it,

759
00:41:41,440 --> 00:41:44,400
Speaker 1: and I think it's a it's a gap sometimes in

760
00:41:44,719 --> 00:41:47,680
Speaker 1: political survey research, particularly on the on the media side

761
00:41:47,680 --> 00:41:49,680
Speaker 1: of things. So this is this is why I said

762
00:41:49,719 --> 00:41:52,160
Speaker 1: it was like Christmas this week. I've been I've been

763
00:41:52,200 --> 00:41:54,279
Speaker 1: going through this data. I'm sure you have as well,

764
00:41:54,360 --> 00:41:57,840
Speaker 1: and so just fair warning, we may geek out a

765
00:41:57,880 --> 00:42:02,160
Speaker 1: little bit here, but before we get to the twenty

766
00:42:02,160 --> 00:42:05,400
Speaker 1: twenty four, I do want to quick because we haven't

767
00:42:05,400 --> 00:42:08,600
Speaker 1: had great data on sort of how the public is

768
00:42:09,120 --> 00:42:14,200
Speaker 1: taking the Iran strikes. So and I'm and look, I

769
00:42:14,760 --> 00:42:19,279
Speaker 1: am a you gov skeptic. It's not my favorite. They're

770
00:42:19,320 --> 00:42:22,319
Speaker 1: not my favorite methodology, I'm not, but there's it's look

771
00:42:22,320 --> 00:42:25,480
Speaker 1: at is ubiquitous, and they do have giant samples, and

772
00:42:25,520 --> 00:42:31,319
Speaker 1: I'll giant sample can sometimes overcome mediocre methodology. So I

773
00:42:31,360 --> 00:42:33,839
Speaker 1: feel like that's been the most data I've seen as

774
00:42:33,840 --> 00:42:36,040
Speaker 1: on that, and it is interesting to me that there

775
00:42:36,080 --> 00:42:38,440
Speaker 1: is some overall skepticism that this is going to be

776
00:42:38,480 --> 00:42:41,160
Speaker 1: long term effective. That's the big takeaway I took is

777
00:42:41,200 --> 00:42:45,319
Speaker 1: that voters really do have an Iraq hangover and how

778
00:42:45,360 --> 00:42:46,080
Speaker 1: they're looking at this.

779
00:42:48,000 --> 00:42:48,600
Speaker 2: Yeah.

780
00:42:48,200 --> 00:42:51,800
Speaker 3: I was fortunate enough to go into the field right

781
00:42:51,960 --> 00:42:57,840
Speaker 3: before the attack on Porto and the other nuclear sites,

782
00:42:58,280 --> 00:43:02,200
Speaker 3: and we asked a pub different questions to me illuminate

783
00:43:02,280 --> 00:43:05,640
Speaker 3: the complexity of public opinion on anything like foreign policy.

784
00:43:05,840 --> 00:43:08,560
Speaker 3: If I ask people for their view on healthcare, oftentimes

785
00:43:08,560 --> 00:43:11,560
Speaker 3: that's pretty straightforward because people deal personally with the healthcare

786
00:43:11,600 --> 00:43:13,920
Speaker 3: system a lot. Or if I ask a question about education,

787
00:43:14,560 --> 00:43:17,240
Speaker 3: you'll get pretty informed views from a lot of people

788
00:43:17,320 --> 00:43:19,359
Speaker 3: because they went through school themselves or they have kids

789
00:43:19,400 --> 00:43:22,040
Speaker 3: in schools. But how many people have day to day

790
00:43:22,160 --> 00:43:26,320
Speaker 3: experiences dealing with how do you stop a RAN's nuclear program?

791
00:43:26,800 --> 00:43:29,279
Speaker 3: And so public opinion on issues like that tends to

792
00:43:29,280 --> 00:43:33,120
Speaker 3: be pretty complicated, at times contradictory.

793
00:43:33,239 --> 00:43:34,440
Speaker 2: So when we asked.

794
00:43:34,120 --> 00:43:37,120
Speaker 3: People about the situation, we asked a couple different questions,

795
00:43:37,320 --> 00:43:39,799
Speaker 3: one of which was just what do you think the

796
00:43:39,920 --> 00:43:43,040
Speaker 3: United States could do when it comes to the conflict

797
00:43:43,239 --> 00:43:46,160
Speaker 3: in the Middle East? And we gave people four different options.

798
00:43:47,040 --> 00:43:51,640
Speaker 3: The options were we should just stay completely out of it,

799
00:43:51,719 --> 00:43:53,960
Speaker 3: we gave them the option of we can stay involved,

800
00:43:54,000 --> 00:43:58,000
Speaker 3: but purely in a diplomatic way. We offered, you can

801
00:43:58,040 --> 00:44:02,600
Speaker 3: get involved through diplomacy and through defending Israel, so we

802
00:44:02,640 --> 00:44:03,680
Speaker 3: can shoot down rockets.

803
00:44:03,680 --> 00:44:05,200
Speaker 2: We just can't shoot rockets of our own.

804
00:44:06,080 --> 00:44:09,520
Speaker 3: And then finally, we should join through joining Israel in

805
00:44:09,760 --> 00:44:13,239
Speaker 3: striking Iranian targets. And when you ask it in that way,

806
00:44:13,360 --> 00:44:16,959
Speaker 3: only eight percent of our respondents chose we should join

807
00:44:17,120 --> 00:44:21,680
Speaker 3: Israel in striking Iranian military targets. You would think, well,

808
00:44:21,719 --> 00:44:23,600
Speaker 3: that's a pretty big sign the public's not going to

809
00:44:23,640 --> 00:44:26,480
Speaker 3: love this. On the other hand, we also then asked

810
00:44:27,200 --> 00:44:31,320
Speaker 3: a sort of forced choice messaging question. I had a

811
00:44:31,320 --> 00:44:34,000
Speaker 3: couple people tweet at me that like, this question is leading,

812
00:44:34,040 --> 00:44:35,920
Speaker 3: and I'm like, yes, both sides of it are leading.

813
00:44:36,000 --> 00:44:38,320
Speaker 2: That's the point. I'm trying to see which side leads

814
00:44:38,360 --> 00:44:38,920
Speaker 2: you harder.

815
00:44:40,200 --> 00:44:43,399
Speaker 3: The options we gave were Iran developing nuclear weapons would

816
00:44:43,440 --> 00:44:45,800
Speaker 3: be an existential threat to the US and its allies,

817
00:44:45,840 --> 00:44:50,840
Speaker 3: and justifies US involvement in supporting Israel versus is Iran

818
00:44:50,880 --> 00:44:53,759
Speaker 3: developing a nuclear weapon is concerning, but not worth the

819
00:44:53,880 --> 00:44:56,200
Speaker 3: US getting involved in another Middle Eastern war. And when

820
00:44:56,239 --> 00:44:59,320
Speaker 3: you ask it that way, but almost a twenty point margin.

821
00:44:59,719 --> 00:45:04,760
Speaker 3: The this justifies our involvement wins. So when you raise

822
00:45:04,840 --> 00:45:07,799
Speaker 3: the specter of we cannot allow Iran to get a

823
00:45:07,840 --> 00:45:12,360
Speaker 3: nuclear weapon, people are like, yeah, you're right, I get it, okay,

824
00:45:12,480 --> 00:45:15,319
Speaker 3: And only about a third are still like Nope, I

825
00:45:15,360 --> 00:45:15,799
Speaker 3: don't care.

826
00:45:15,920 --> 00:45:17,640
Speaker 2: I'm out on this. I don't want anything to do

827
00:45:17,719 --> 00:45:18,000
Speaker 2: with it.

828
00:45:18,280 --> 00:45:20,200
Speaker 3: But when it comes down to the specifics of what

829
00:45:20,320 --> 00:45:23,960
Speaker 3: people want the US's involvement to look like, that's where

830
00:45:24,400 --> 00:45:28,560
Speaker 3: US directly striking Iran was not something voters were clamoring

831
00:45:28,640 --> 00:45:32,360
Speaker 3: for beforehand. Now, I always think of Donald Trump as

832
00:45:33,520 --> 00:45:35,600
Speaker 3: if you're ever like doing your dishes and there's like

833
00:45:35,640 --> 00:45:36,960
Speaker 3: a pot in the sink that has a lot of

834
00:45:36,960 --> 00:45:38,400
Speaker 3: oil in it, you put the dish soap in, and

835
00:45:38,440 --> 00:45:40,120
Speaker 3: all of sudden, all the oil like spreads out to

836
00:45:40,160 --> 00:45:43,239
Speaker 3: the sides. Like that's exactly what Donald Trump is. Every

837
00:45:43,239 --> 00:45:45,520
Speaker 3: time he does something, all of a sudden, he's like

838
00:45:45,560 --> 00:45:47,760
Speaker 3: the dish soap and everything spreads out to the sides.

839
00:45:48,040 --> 00:45:50,440
Speaker 2: So suddenly people who were really anti.

840
00:45:50,160 --> 00:45:54,960
Speaker 3: War before, but their maga through and through a lot

841
00:45:55,000 --> 00:45:56,400
Speaker 3: of them came around to being like, you know what,

842
00:45:56,440 --> 00:45:59,560
Speaker 3: this actually was the smartest presidential decision ever made, and

843
00:45:59,600 --> 00:46:02,400
Speaker 3: so and so forth. So I suspect the pulling on

844
00:46:02,440 --> 00:46:06,600
Speaker 3: this school move into established parties in camps pretty quickly.

845
00:46:07,440 --> 00:46:09,480
Speaker 1: And so what do you think is the more effective

846
00:46:10,200 --> 00:46:16,160
Speaker 1: of what's the more if we if in a month

847
00:46:16,600 --> 00:46:19,520
Speaker 1: we have it in the expected camps, then is that

848
00:46:19,680 --> 00:46:23,840
Speaker 1: data that's worthy or do you actually learn more from

849
00:46:25,320 --> 00:46:28,040
Speaker 1: what you the measurements you did sort of in the

850
00:46:28,120 --> 00:46:31,520
Speaker 1: run up and in the immediate aftermath, because it is

851
00:46:31,560 --> 00:46:35,040
Speaker 1: when people were a little bit more fluid in their thinking,

852
00:46:35,160 --> 00:46:38,880
Speaker 1: Like what gives you more insight on if you were

853
00:46:38,920 --> 00:46:42,160
Speaker 1: trying to use the data to make a decision on

854
00:46:42,320 --> 00:46:43,640
Speaker 1: persuasion in a campaign.

855
00:46:45,920 --> 00:46:48,840
Speaker 3: I mean I would be interested in seeing which groups

856
00:46:49,080 --> 00:46:53,000
Speaker 3: shift the most, So for instance, among Republicans you know

857
00:46:53,080 --> 00:46:56,239
Speaker 3: in our data even before the strikes. We love to

858
00:46:56,280 --> 00:46:58,560
Speaker 3: ask this question, do you think of yourself as a

859
00:46:58,640 --> 00:47:02,160
Speaker 3: Trump supporter first and foremost or as a Republican Party

860
00:47:02,160 --> 00:47:05,080
Speaker 3: supporter first and foremost? And I think the conventional wisdom

861
00:47:05,160 --> 00:47:07,800
Speaker 3: is that if you are more of a trumpy person

862
00:47:08,000 --> 00:47:11,719
Speaker 3: than a party first person, more nicky Hailey.

863
00:47:11,440 --> 00:47:14,160
Speaker 1: Type of what break down these days inside the party

864
00:47:14,280 --> 00:47:16,640
Speaker 1: like because that ebbs and flows, it's been you know

865
00:47:16,680 --> 00:47:18,640
Speaker 1: we've done this, that we've been doing I say we.

866
00:47:18,880 --> 00:47:20,600
Speaker 2: I'm no longer running the NBC poll.

867
00:47:20,600 --> 00:47:24,640
Speaker 1: But when Trump was down, it would be forty sixty

868
00:47:24,680 --> 00:47:26,719
Speaker 1: in favor of Republicans, and when Trump would be up,

869
00:47:26,760 --> 00:47:30,000
Speaker 1: it would be essentially sixty forty. I'm being estimate, But

870
00:47:30,040 --> 00:47:31,480
Speaker 1: where are you? Where's your dial?

871
00:47:31,600 --> 00:47:34,479
Speaker 2: These days? On that it's closer to sixty forty.

872
00:47:34,480 --> 00:47:36,200
Speaker 3: I want to get you the exact number, because I

873
00:47:36,239 --> 00:47:38,560
Speaker 3: don't want to just guess, but I believe it was

874
00:47:38,560 --> 00:47:42,640
Speaker 3: something like in the high fifties for Trump first, and

875
00:47:42,719 --> 00:47:46,640
Speaker 3: it was in the maybe high thirties, Yes, okay, fifty

876
00:47:46,680 --> 00:47:49,880
Speaker 3: six percent supporter of Donald Trump, thirty seven percent supporter

877
00:47:50,000 --> 00:47:53,480
Speaker 3: of the Republican Party, three percent. I don't really support

878
00:47:53,520 --> 00:47:56,800
Speaker 3: either one three percent, I'm sure, So it's still and

879
00:47:57,040 --> 00:48:00,880
Speaker 3: you're right, this is a number much more so then

880
00:48:01,680 --> 00:48:05,680
Speaker 3: Republican just identification in general, that has moved around a ton.

881
00:48:05,719 --> 00:48:08,680
Speaker 3: When he was an exile in Marlago, there was a

882
00:48:08,680 --> 00:48:10,799
Speaker 3: time when it was only like one in four Republicans

883
00:48:10,840 --> 00:48:13,480
Speaker 3: still thought of themselves as like diehard Trump people.

884
00:48:14,520 --> 00:48:16,960
Speaker 2: But when the more he is in the news, the

885
00:48:16,960 --> 00:48:19,160
Speaker 2: more Republicans rally around him, the more they think of

886
00:48:19,280 --> 00:48:20,920
Speaker 2: him as the person they rally around.

887
00:48:23,239 --> 00:48:29,319
Speaker 1: So is it your mindset that Iran is still would

888
00:48:29,320 --> 00:48:31,879
Speaker 1: you call it unsettled data?

889
00:48:31,960 --> 00:48:32,440
Speaker 2: Right? Yes?

890
00:48:32,520 --> 00:48:37,359
Speaker 3: And I think the the intelligence estimates of what did

891
00:48:37,400 --> 00:48:42,160
Speaker 3: we actually achieve? I think there's a reason why Donald

892
00:48:42,200 --> 00:48:46,279
Speaker 3: Trump is in is so angry about that report from

893
00:48:46,280 --> 00:48:50,879
Speaker 3: earlier this week that the Defense Intelligence Agency says maybe

894
00:48:50,880 --> 00:48:55,200
Speaker 3: actually not that much damage was done because the whole

895
00:48:55,239 --> 00:48:58,480
Speaker 3: purpose of doing this is that you have addressed in

896
00:48:58,520 --> 00:49:01,520
Speaker 3: that that question where people are we're getting messaging, you

897
00:49:01,560 --> 00:49:03,680
Speaker 3: have addressed the existential threat. If you have not addressed

898
00:49:03,680 --> 00:49:07,000
Speaker 3: the existential threat, then what was the point? And so

899
00:49:07,440 --> 00:49:10,440
Speaker 3: that's why I think there's been I think the polling

900
00:49:10,480 --> 00:49:13,440
Speaker 3: on this is all going to hinge on what did

901
00:49:13,440 --> 00:49:14,640
Speaker 3: we actually achieve there?

902
00:49:15,800 --> 00:49:19,279
Speaker 1: So let's go to our are this fun little like

903
00:49:19,320 --> 00:49:21,960
Speaker 1: I said summer Christmas gift for data geeks that came

904
00:49:21,960 --> 00:49:27,200
Speaker 1: out from Pew and sort of it's easily the most grangular.

905
00:49:27,239 --> 00:49:29,759
Speaker 1: It's basically the best version of an exit poll as

906
00:49:29,760 --> 00:49:34,359
Speaker 1: you can get. Look, I thought most of mainstream media

907
00:49:34,400 --> 00:49:37,839
Speaker 1: got the wrong headline the headline, and I thought Pugh

908
00:49:38,040 --> 00:49:41,600
Speaker 1: led with the wrong thing right. Their headline was simply hey,

909
00:49:41,719 --> 00:49:44,640
Speaker 1: a higher turnout would have benefited Trump more than it

910
00:49:44,640 --> 00:49:46,880
Speaker 1: would have benefitted Harris. And I didn't think that was

911
00:49:46,920 --> 00:49:48,880
Speaker 1: a new insight. I feel like that we kind of

912
00:49:49,160 --> 00:49:52,000
Speaker 1: we've known this for a couple of cycles.

913
00:49:52,040 --> 00:49:52,239
Speaker 2: Now.

914
00:49:53,200 --> 00:49:58,239
Speaker 1: For me, the biggest headline is the Hispanic number, the

915
00:49:58,280 --> 00:50:03,680
Speaker 1: fifty one forty eight. That is the oh wow type

916
00:50:03,680 --> 00:50:05,840
Speaker 1: of result. I mean, we knew it was close to

917
00:50:05,920 --> 00:50:08,319
Speaker 1: the question was I didn't you know? I don't think

918
00:50:08,360 --> 00:50:10,640
Speaker 1: any of us thought it was that narrow.

919
00:50:12,719 --> 00:50:17,720
Speaker 3: Yeah, the fact that the Trump coalition was made up of,

920
00:50:18,920 --> 00:50:22,920
Speaker 3: you know, twenty two percent voters who were not white

921
00:50:23,239 --> 00:50:30,200
Speaker 3: is actually huge for a Republican presidential candidates. And I've

922
00:50:30,239 --> 00:50:33,719
Speaker 3: been thinking a lot about where our politics were ten

923
00:50:33,800 --> 00:50:37,399
Speaker 3: years ago lately, in part because it's been ten years

924
00:50:37,440 --> 00:50:40,680
Speaker 3: since Donald Trump went down the Bolten escalator. It's been

925
00:50:40,719 --> 00:50:43,160
Speaker 3: ten years since I wrote my book about Republicans should

926
00:50:43,160 --> 00:50:45,600
Speaker 3: do to win vacuum voters that didn't mention Donald Trump

927
00:50:45,640 --> 00:50:49,399
Speaker 3: and like exists in some parallel alternate universe where none

928
00:50:49,400 --> 00:50:53,400
Speaker 3: of the last ten years ever happened. But also I

929
00:50:53,440 --> 00:50:55,359
Speaker 3: think back a lot to that period of time where

930
00:50:55,400 --> 00:51:00,439
Speaker 3: Republicans were in such a panic about their poor performance

931
00:51:00,800 --> 00:51:04,480
Speaker 3: with working class voters, poor performance with voters of color,

932
00:51:04,880 --> 00:51:08,120
Speaker 3: poor performance with suburban voters, poor performance with younger voters.

933
00:51:08,160 --> 00:51:10,120
Speaker 1: And you're really referring to twenty twelve. I mean twenty

934
00:51:10,120 --> 00:51:11,400
Speaker 1: twelve was the peak of all of that.

935
00:51:12,239 --> 00:51:14,920
Speaker 2: Yes, and you had, you know, in the aftermath of that,

936
00:51:15,000 --> 00:51:18,120
Speaker 2: then you had the autopsy.

937
00:51:19,320 --> 00:51:22,160
Speaker 3: You then had Eric Canter losing in the summer of

938
00:51:22,160 --> 00:51:24,800
Speaker 3: twenty fourteen, and that kind of being like, oh my gosh,

939
00:51:24,840 --> 00:51:27,800
Speaker 3: not only is our party not moving back to the center,

940
00:51:28,040 --> 00:51:31,319
Speaker 3: we now have this base that is putting seats at

941
00:51:31,360 --> 00:51:33,480
Speaker 3: jeopardy by taking over primaries.

942
00:51:33,800 --> 00:51:35,520
Speaker 2: I have thought a lot about that this week with

943
00:51:35,560 --> 00:51:37,239
Speaker 2: regards to you, everything that happened in New York.

944
00:51:37,280 --> 00:51:40,479
Speaker 1: But my favorite sweet impact I quoted you. I used

945
00:51:40,480 --> 00:51:45,760
Speaker 1: you earlier in my monologue about how you were having

946
00:51:46,200 --> 00:51:49,920
Speaker 1: flashbacks at the anonymous census Democrat who was going, We're

947
00:51:49,920 --> 00:51:52,640
Speaker 1: going to nominate these crazy people have crazy ideas, and

948
00:51:52,680 --> 00:51:53,840
Speaker 1: the we're never going to get them done, and then

949
00:51:53,880 --> 00:51:55,319
Speaker 1: voters are going to hate us even more. And it

950
00:51:55,360 --> 00:51:58,360
Speaker 1: was like that was every Tea Party candidate right in

951
00:51:58,400 --> 00:51:59,160
Speaker 1: twenty fourteen.

952
00:51:59,760 --> 00:52:03,239
Speaker 3: Yeah, and every Republican strategist was panicking that we were

953
00:52:03,280 --> 00:52:05,760
Speaker 3: never going to win elections again, and then we did.

954
00:52:06,239 --> 00:52:08,759
Speaker 3: And that, to me is the thing that has been

955
00:52:08,800 --> 00:52:13,399
Speaker 3: the most surprising is someone like me eight years ago

956
00:52:13,760 --> 00:52:16,440
Speaker 3: was completely hair on fire that Donald Trump is going

957
00:52:16,520 --> 00:52:19,160
Speaker 3: to take everything that our party has been doing to

958
00:52:19,239 --> 00:52:21,680
Speaker 3: try to win over young voters or voters of color,

959
00:52:21,719 --> 00:52:23,759
Speaker 3: and he is lighting it all on fire and it

960
00:52:23,840 --> 00:52:27,640
Speaker 3: is going to be unrecoverable. And now, if I am

961
00:52:27,680 --> 00:52:31,600
Speaker 3: a person that follows the data, you cannot. Now you

962
00:52:31,680 --> 00:52:34,400
Speaker 3: have to acknowledge that those are the very groups that

963
00:52:34,480 --> 00:52:39,000
Speaker 3: he put his reelection. He built it on those groups,

964
00:52:39,160 --> 00:52:42,799
Speaker 3: and it did better with Latino voters, better with younger

965
00:52:42,880 --> 00:52:45,040
Speaker 3: voters than any Republican has in twenty years.

966
00:52:45,200 --> 00:52:46,799
Speaker 2: And that's really remarkable.

967
00:52:49,239 --> 00:52:51,160
Speaker 1: It's funny you bring up twenty years ago because I

968
00:52:51,200 --> 00:52:55,160
Speaker 1: did a little tweet on this that it is fascinating

969
00:52:55,160 --> 00:53:00,399
Speaker 1: to me that at least on race and ethnicity, twenty

970
00:53:00,440 --> 00:53:03,960
Speaker 1: four election actually looks more like twenty oh four than

971
00:53:04,200 --> 00:53:07,359
Speaker 1: any other election, And it looks more like twenty oh

972
00:53:07,440 --> 00:53:09,480
Speaker 1: four than any other election this century.

973
00:53:09,960 --> 00:53:12,440
Speaker 2: And in twenty oh four, George W.

974
00:53:12,480 --> 00:53:15,360
Speaker 1: Bush was getting double digits support among African Americans. In

975
00:53:15,400 --> 00:53:19,040
Speaker 1: twenty oh four, you know, whichever exit poll you want

976
00:53:19,040 --> 00:53:21,080
Speaker 1: to believe is that forty four percent of Latinos. I

977
00:53:21,120 --> 00:53:24,560
Speaker 1: think we've maybe now I think, accepted the premise that

978
00:53:24,600 --> 00:53:27,000
Speaker 1: it was forty four percent. Democrats kept saying, oh, it

979
00:53:27,040 --> 00:53:29,319
Speaker 1: was only forty Okay, you want to have this fight

980
00:53:29,520 --> 00:53:34,640
Speaker 1: like it was. It was a lot and I've been

981
00:53:34,680 --> 00:53:38,239
Speaker 1: trying to Now, that doesn't mean the electorate. You know,

982
00:53:38,680 --> 00:53:40,960
Speaker 1: it's different by education than it was twenty years ago.

983
00:53:41,520 --> 00:53:43,719
Speaker 1: But what do you make because there's a there's a

984
00:53:43,760 --> 00:53:47,560
Speaker 1: part of me that it's believed that the Obama coalition

985
00:53:47,640 --> 00:53:51,480
Speaker 1: was an outlier. The Obama coalition was special to Obama

986
00:53:51,520 --> 00:53:54,160
Speaker 1: for a variety of reasons. And what's interesting to me

987
00:53:54,239 --> 00:53:56,520
Speaker 1: is it's sort of like, did we go this is

988
00:53:56,520 --> 00:53:59,480
Speaker 1: what our electorate looked like pre Obama And it took

989
00:53:59,640 --> 00:54:02,279
Speaker 1: he said, actually ten years post Obama to get back

990
00:54:02,560 --> 00:54:05,400
Speaker 1: to what the electorate looked like pre Obama. What do

991
00:54:05,440 --> 00:54:07,279
Speaker 1: you make of that? So?

992
00:54:07,320 --> 00:54:09,399
Speaker 3: I think there are a couple of things that are

993
00:54:09,640 --> 00:54:14,640
Speaker 3: a little bit that are still different today. One is

994
00:54:14,800 --> 00:54:17,720
Speaker 3: that you still see I think you see younger people

995
00:54:17,840 --> 00:54:22,360
Speaker 3: interacting with politics in a fundamentally different way today that

996
00:54:22,480 --> 00:54:25,919
Speaker 3: they did in two thousand and four. I also think,

997
00:54:26,120 --> 00:54:28,680
Speaker 3: you know, just the share of the electorate that is

998
00:54:28,800 --> 00:54:34,640
Speaker 3: non white has continued to grow, sort of separately from

999
00:54:34,800 --> 00:54:37,720
Speaker 3: the ebbs and flows of an Obama presidency, maybe turning

1000
00:54:37,719 --> 00:54:40,200
Speaker 3: out an especially high number of black voters or something

1001
00:54:40,280 --> 00:54:43,960
Speaker 3: like that, where that was supposed to be the defnell

1002
00:54:44,000 --> 00:54:47,160
Speaker 3: of the Republicans, that if Republicans could not figure out

1003
00:54:47,200 --> 00:54:51,080
Speaker 3: how to overcome a rising share of the electric made

1004
00:54:51,120 --> 00:54:53,160
Speaker 3: up from the millennial generation, or a rising share of

1005
00:54:53,160 --> 00:54:55,040
Speaker 3: the electric made up of Latinos, they were going to

1006
00:54:55,080 --> 00:54:59,880
Speaker 3: be washed out. And Republicans have figured some of that out.

1007
00:55:00,400 --> 00:55:02,960
Speaker 3: So I think it's not necessarily I don't think we're

1008
00:55:03,040 --> 00:55:04,560
Speaker 3: fully back in two thousand and four.

1009
00:55:04,680 --> 00:55:05,200
Speaker 2: I know the.

1010
00:55:05,080 --> 00:55:07,640
Speaker 3: Fashion that we that the kids these days are wearing

1011
00:55:07,760 --> 00:55:09,960
Speaker 3: is I know the music. I know we've like really

1012
00:55:09,960 --> 00:55:10,560
Speaker 3: gone back.

1013
00:55:11,160 --> 00:55:15,600
Speaker 2: My eighteen year old likes Oasis. I'm like Oasis. How

1014
00:55:15,600 --> 00:55:16,160
Speaker 2: did this happen?

1015
00:55:16,160 --> 00:55:16,279
Speaker 1: Oh?

1016
00:55:16,320 --> 00:55:18,520
Speaker 2: That's good. They can be a lot worse. That could

1017
00:55:18,520 --> 00:55:19,240
Speaker 2: be a lot worse.

1018
00:55:19,520 --> 00:55:21,920
Speaker 1: It could be, but you're right, like a little late

1019
00:55:22,040 --> 00:55:29,760
Speaker 1: nineties early Yeah, that's funny. Well it's here. Was another

1020
00:55:30,040 --> 00:55:32,560
Speaker 1: thing though, that I was wondering and looking through the data.

1021
00:55:33,560 --> 00:55:38,759
Speaker 1: When Democrats go about targeting and messaging they actually think

1022
00:55:38,840 --> 00:55:42,200
Speaker 1: demographically all the time with their messaging, and they tell you, right,

1023
00:55:42,200 --> 00:55:44,800
Speaker 1: they telegraph it. This is how we're going to appeal

1024
00:55:44,840 --> 00:55:46,680
Speaker 1: to Latino voters, and this is how we're appealing to

1025
00:55:46,719 --> 00:55:48,480
Speaker 1: black voters. And we've got to appeal to black men,

1026
00:55:48,520 --> 00:55:51,600
Speaker 1: and we've got appeal to this blah blah blah blah blah.

1027
00:55:52,600 --> 00:55:54,640
Speaker 1: I'll hear some of that on the Republican side of

1028
00:55:54,680 --> 00:55:57,360
Speaker 1: the AISL but not nearly as much. And I'm I'm wondering,

1029
00:55:57,480 --> 00:56:02,520
Speaker 1: are we overrating? Like we make all these efforts to

1030
00:56:02,560 --> 00:56:05,600
Speaker 1: look at these splits when everything moved in the same direction.

1031
00:56:06,160 --> 00:56:09,120
Speaker 1: You know, we like, take black men, there was this obsession,

1032
00:56:09,120 --> 00:56:11,359
Speaker 1: oh my god, she's doing terribly with black men. Well,

1033
00:56:11,360 --> 00:56:13,160
Speaker 1: what if I told you he also doubled his support

1034
00:56:13,160 --> 00:56:15,960
Speaker 1: among black women. So, like my point is that this

1035
00:56:16,080 --> 00:56:19,400
Speaker 1: wasn't just a black male issue. This was just he

1036
00:56:19,480 --> 00:56:22,320
Speaker 1: doubled his support among black voters hard stop. He doubled

1037
00:56:22,360 --> 00:56:25,040
Speaker 1: it among black men, and he doubled it among black women.

1038
00:56:25,400 --> 00:56:28,200
Speaker 1: And you see it across the board that this there

1039
00:56:28,239 --> 00:56:34,040
Speaker 1: isn't I didn't find one individual demographic group that you say, oh,

1040
00:56:34,280 --> 00:56:40,000
Speaker 1: this is the explanation when he basically improved across the board,

1041
00:56:40,520 --> 00:56:45,080
Speaker 1: which makes me think that the xylophone approach of the Democrats,

1042
00:56:45,120 --> 00:56:47,279
Speaker 1: which is we're going to message over on this to

1043
00:56:47,360 --> 00:56:49,080
Speaker 1: this group of people and on this to this group

1044
00:56:49,120 --> 00:56:53,400
Speaker 1: of people, was a complete nutter failure and the message

1045
00:56:53,440 --> 00:56:55,840
Speaker 1: to everybody approach was more effective.

1046
00:56:57,560 --> 00:57:02,279
Speaker 2: Yeah, I think that's right, But I also so think going.

1047
00:57:02,120 --> 00:57:07,760
Speaker 3: After voters in cities were like, going after places where

1048
00:57:07,920 --> 00:57:10,760
Speaker 3: Democrats had made such in roads over the last twenty

1049
00:57:10,840 --> 00:57:12,520
Speaker 3: years that there was like there was room for the

1050
00:57:12,560 --> 00:57:17,480
Speaker 3: pide to come back out was pretty smart. We took

1051
00:57:17,520 --> 00:57:20,840
Speaker 3: a look at, you know, counties, so not individual people,

1052
00:57:20,880 --> 00:57:24,120
Speaker 3: but counties demographically to see where the shift was. And

1053
00:57:24,160 --> 00:57:27,920
Speaker 3: when I give presentations to my clients or other audiences

1054
00:57:27,920 --> 00:57:30,600
Speaker 3: about what happened in twenty twenty four, you know, I say,

1055
00:57:30,640 --> 00:57:33,080
Speaker 3: everybody talks about how polarized we are as a country

1056
00:57:33,120 --> 00:57:35,320
Speaker 3: and how it feels like red and Blue America or

1057
00:57:35,360 --> 00:57:37,800
Speaker 3: splitting further and further apart. What if we told you

1058
00:57:37,840 --> 00:57:39,640
Speaker 3: this was an election where we actually saw some of

1059
00:57:39,640 --> 00:57:42,320
Speaker 3: that polarization shrink and people are like, what are you

1060
00:57:42,400 --> 00:57:45,280
Speaker 3: talking about, And it's like, yeah, did you know that

1061
00:57:45,360 --> 00:57:49,800
Speaker 3: actually urban voters like urban counties swung more to the right,

1062
00:57:50,360 --> 00:57:54,080
Speaker 3: and so therefore the distance. But in voting behavior between

1063
00:57:54,960 --> 00:57:57,680
Speaker 3: the center of a big city and the most rural

1064
00:57:57,680 --> 00:58:00,000
Speaker 3: county you can think of, like they are slightly less

1065
00:58:00,040 --> 00:58:03,280
Speaker 3: different in how they voted. Counties that are very diverse

1066
00:58:03,320 --> 00:58:06,200
Speaker 3: and counties that are super white voted a little more

1067
00:58:06,240 --> 00:58:07,920
Speaker 3: like one another this time. I mean the fact that

1068
00:58:07,960 --> 00:58:12,520
Speaker 3: Donald Trump improved his numbers everywhere meant that, like, you

1069
00:58:12,600 --> 00:58:15,920
Speaker 3: didn't see the gender gap grow, if anything, you saw trink.

1070
00:58:16,280 --> 00:58:20,360
Speaker 3: You didn't see the age gap grow, if anything, you

1071
00:58:20,400 --> 00:58:22,200
Speaker 3: saw trink. And so you go through all of these

1072
00:58:22,200 --> 00:58:25,640
Speaker 3: demographics and there isn't in the only one where there

1073
00:58:25,680 --> 00:58:30,560
Speaker 3: was polarization that did get worse was a little bit

1074
00:58:30,720 --> 00:58:35,520
Speaker 3: like white college versus white non college. But I mean

1075
00:58:35,520 --> 00:58:37,720
Speaker 3: we're talking like two or three points if you're looking

1076
00:58:37,800 --> 00:58:41,000
Speaker 3: at the like the network exit polls. Sure, I mean

1077
00:58:41,080 --> 00:58:44,280
Speaker 3: it's just that's the only place where you may have

1078
00:58:44,400 --> 00:58:47,320
Speaker 3: seen some slight widening of the gap.

1079
00:58:47,680 --> 00:58:49,360
Speaker 1: Well that back up your urban point, you know, and

1080
00:58:49,400 --> 00:58:53,400
Speaker 1: there it is interesting that let's just take African American voters.

1081
00:58:53,440 --> 00:58:56,960
Speaker 1: Hillary Clinton won of by eighty five percentage points, Kamala

1082
00:58:57,000 --> 00:59:01,240
Speaker 1: Harris one of by sixty eight, like that's that's the swing, Like.

1083
00:59:01,160 --> 00:59:04,200
Speaker 2: That was a swing. But these swings were across the board.

1084
00:59:04,200 --> 00:59:06,680
Speaker 2: It wasn't just black voters. It was young voters. It

1085
00:59:06,720 --> 00:59:07,960
Speaker 2: was And so.

1086
00:59:09,720 --> 00:59:13,120
Speaker 1: If you were if you were looking at this, would

1087
00:59:13,120 --> 00:59:16,760
Speaker 1: you say the Democratic Party had demographic issue or would

1088
00:59:16,760 --> 00:59:18,200
Speaker 1: you say they have a messaging issue.

1089
00:59:20,400 --> 00:59:24,080
Speaker 3: I would say it's a messaging issue first and foremost,

1090
00:59:24,200 --> 00:59:27,720
Speaker 3: because I am not yet convinced that all of those

1091
00:59:27,800 --> 00:59:34,360
Speaker 3: voters are Republican voters forever and ever and ever. You know,

1092
00:59:34,400 --> 00:59:36,240
Speaker 3: if you look, one of the things that's so valuable

1093
00:59:36,280 --> 00:59:38,360
Speaker 3: about that Pew study is they can look at people

1094
00:59:38,360 --> 00:59:41,760
Speaker 3: who are validated voters in twenty twenty and in twenty

1095
00:59:41,800 --> 00:59:44,920
Speaker 3: twenty four, or people who didn't vote in one of

1096
00:59:44,960 --> 00:59:48,680
Speaker 3: those two elections and sort of match up, you know,

1097
00:59:48,880 --> 00:59:53,280
Speaker 3: how did people blow And it's not the case that

1098
00:59:53,360 --> 00:59:56,400
Speaker 3: you know that a bunch of people who voted for

1099
00:59:57,280 --> 01:00:00,600
Speaker 3: Joe Biden last time all swung to vote.

1100
01:00:00,400 --> 01:00:01,440
Speaker 2: For Trump, like some of them.

1101
01:00:01,480 --> 01:00:05,240
Speaker 3: Did you know five percent of Biden's voters became Trump voters,

1102
01:00:05,440 --> 01:00:08,400
Speaker 3: but three percent of Trump's twenty twenty voters became Harris voters.

1103
01:00:08,400 --> 01:00:10,040
Speaker 3: So you know, there was a little bit of switching

1104
01:00:10,040 --> 01:00:13,200
Speaker 3: off there. To me, the bigger story is an awful

1105
01:00:13,240 --> 01:00:15,760
Speaker 3: lot of Biden twenty twenty voters just didn't vote.

1106
01:00:16,160 --> 01:00:18,120
Speaker 1: That's the biggest story out of this. It's who didn't

1107
01:00:18,160 --> 01:00:19,200
Speaker 1: show up appearances.

1108
01:00:19,320 --> 01:00:22,160
Speaker 2: Yeah, that's that's all. That's the whole game.

1109
01:00:22,280 --> 01:00:24,760
Speaker 3: And then of people who didn't vote in twenty twenty,

1110
01:00:25,480 --> 01:00:28,200
Speaker 3: Trump did a little better among those folks, and that

1111
01:00:28,320 --> 01:00:33,160
Speaker 3: to me, the Democratic Coalition just failing to excite and

1112
01:00:33,320 --> 01:00:38,200
Speaker 3: turn out people who had voted for Biden before but

1113
01:00:38,280 --> 01:00:41,160
Speaker 3: this time said I am not dealing with this, no,

1114
01:00:41,280 --> 01:00:45,680
Speaker 3: thank you, I'm not interested, was really striking. I don't

1115
01:00:45,680 --> 01:00:47,720
Speaker 3: think that that gives a clear answer though, to the

1116
01:00:47,800 --> 01:00:50,560
Speaker 3: question of like what should Democrats have done, because again

1117
01:00:50,600 --> 01:00:53,680
Speaker 3: to the idea that this is like a repeat of

1118
01:00:53,720 --> 01:00:56,680
Speaker 3: the Republican identity crisis of you know, a decade or

1119
01:00:56,720 --> 01:01:00,280
Speaker 3: twelve years ago, the question is, well, did those people

1120
01:01:00,320 --> 01:01:04,040
Speaker 3: not turn out because we were insufficiently progressive, because we

1121
01:01:04,160 --> 01:01:07,760
Speaker 3: tried too hard to win over those Liz Cheney Republicans

1122
01:01:07,880 --> 01:01:10,320
Speaker 3: and we didn't, you know, go far enough to the

1123
01:01:10,400 --> 01:01:13,720
Speaker 3: left on Gaza Or is the problem that we went

1124
01:01:13,840 --> 01:01:16,320
Speaker 3: too far to the left on the woke stuff, that

1125
01:01:16,360 --> 01:01:18,800
Speaker 3: we went too far to the left on spending, and

1126
01:01:18,840 --> 01:01:21,560
Speaker 3: we got too captive by the progressives and Republicans went

1127
01:01:21,600 --> 01:01:24,120
Speaker 3: through the same thing. Is the problem that we were

1128
01:01:24,160 --> 01:01:26,840
Speaker 3: too conservative? Is the problem that we weren't conservative enough?

1129
01:01:27,520 --> 01:01:29,960
Speaker 1: Well, nobody in twenty thirteen would have said, you know,

1130
01:01:30,000 --> 01:01:33,560
Speaker 1: the answer for Republicans to recover is to double down

1131
01:01:33,560 --> 01:01:37,840
Speaker 1: on immigration and get tougher, And yet that turned out

1132
01:01:37,880 --> 01:01:41,240
Speaker 1: to be the right call. Just politically. I'm not going

1133
01:01:41,240 --> 01:01:42,920
Speaker 1: to say here, we're not making I'm not making a

1134
01:01:43,000 --> 01:01:46,440
Speaker 1: judgment of policy. But politically it turned out every instinct

1135
01:01:46,480 --> 01:01:48,400
Speaker 1: of the autopsy was exactly wrong.

1136
01:01:50,200 --> 01:01:51,360
Speaker 2: Let me push back on that.

1137
01:01:51,880 --> 01:01:55,160
Speaker 3: So the instinct about immigration, to the extent that immigration

1138
01:01:55,680 --> 01:01:58,520
Speaker 3: is like the main thing people remember from the autopsy,

1139
01:01:59,040 --> 01:02:01,840
Speaker 3: you are right, the politics of immigration over the intervening

1140
01:02:01,880 --> 01:02:04,880
Speaker 3: decade have changed a lot where that is no longer clearly.

1141
01:02:04,960 --> 01:02:06,480
Speaker 3: In fact, the opposite is the way that you would

1142
01:02:06,480 --> 01:02:09,040
Speaker 3: go about winning Latino voters. But something that I think

1143
01:02:09,040 --> 01:02:11,720
Speaker 3: people don't really remember as much is that a lot

1144
01:02:11,760 --> 01:02:15,439
Speaker 3: of stuff in that autopsy where things like get better

1145
01:02:15,440 --> 01:02:18,120
Speaker 3: about meeting voters, where they are using data in digital

1146
01:02:18,120 --> 01:02:22,440
Speaker 3: to target them more effectively, go find unconventional audiences, Go

1147
01:02:22,520 --> 01:02:25,440
Speaker 3: get more engaged in pop culture and so weirdly, like

1148
01:02:25,520 --> 01:02:29,120
Speaker 3: I went back to reread that document not too long ago,

1149
01:02:29,680 --> 01:02:32,960
Speaker 3: and it actually holds up better than you'd think, because weirdly,

1150
01:02:33,000 --> 01:02:35,480
Speaker 3: Donald Trump does a lot of those tactical things that

1151
01:02:35,560 --> 01:02:38,640
Speaker 3: don't sound as sexy as the party needs to moderate

1152
01:02:38,640 --> 01:02:41,360
Speaker 3: on immigration, the main thing people remember, he actually did

1153
01:02:41,400 --> 01:02:44,120
Speaker 3: a lot of it, and it finally, you know.

1154
01:02:44,160 --> 01:02:46,080
Speaker 2: It bared fruit.

1155
01:02:48,520 --> 01:02:50,919
Speaker 1: Let's look at the Mom Donnie victory in New York,

1156
01:02:50,960 --> 01:02:54,080
Speaker 1: and I'm curious because there's definitely there's a bunch of

1157
01:02:54,160 --> 01:02:56,200
Speaker 1: ways you can look at it, right, this argument about

1158
01:02:56,280 --> 01:02:59,360
Speaker 1: should they have been more progressive or was it?

1159
01:02:59,680 --> 01:03:01,000
Speaker 2: Was it something else?

1160
01:03:01,200 --> 01:03:04,160
Speaker 1: And the thing is, I think it's too soon to

1161
01:03:04,200 --> 01:03:07,880
Speaker 1: know what the exact answer is because you can easily say, well,

1162
01:03:08,800 --> 01:03:12,680
Speaker 1: Mom Donnie was talking about the issues voters were talking about,

1163
01:03:12,680 --> 01:03:15,720
Speaker 1: which was cost of living. Sounds familiar. Trump was talking

1164
01:03:15,760 --> 01:03:18,120
Speaker 1: about the issues that voters are talking about cost of living,

1165
01:03:19,200 --> 01:03:22,680
Speaker 1: and Cuomo was talking about Donald Trump. Kamala Harris was

1166
01:03:22,680 --> 01:03:27,200
Speaker 1: talking about Donald Trump, right, like, is it it's possible

1167
01:03:27,720 --> 01:03:30,400
Speaker 1: that's the explanation. Again, I don't think we know the

1168
01:03:30,440 --> 01:03:32,600
Speaker 1: answer yet until we see more of this proof. If

1169
01:03:32,600 --> 01:03:36,240
Speaker 1: we see people trying to replicate Mam Donnie on policy,

1170
01:03:36,240 --> 01:03:40,080
Speaker 1: not just on tactics, but on democratic socialism, right, And

1171
01:03:40,280 --> 01:03:44,320
Speaker 1: you know, I am because of the example of Donald Trump.

1172
01:03:44,760 --> 01:03:46,680
Speaker 1: I'm not going to sit here and say for sure

1173
01:03:47,200 --> 01:03:50,600
Speaker 1: that isn't going to work given what we just discussed. Now,

1174
01:03:50,800 --> 01:03:52,560
Speaker 1: I look at what happened to the state of Florida

1175
01:03:53,080 --> 01:03:56,120
Speaker 1: when they introduced democratic socialism, and it turned a swing

1176
01:03:56,160 --> 01:03:59,040
Speaker 1: state into a red state literally in six years. So

1177
01:03:59,680 --> 01:04:03,760
Speaker 1: that's that's my example of why I assume this doesn't work.

1178
01:04:04,480 --> 01:04:06,640
Speaker 1: But I don't want to make those assumptions because hey,

1179
01:04:06,680 --> 01:04:10,120
Speaker 1: Donald Trump up up ended the table. How do you

1180
01:04:10,240 --> 01:04:14,160
Speaker 1: see the result and what do you think was probably

1181
01:04:14,200 --> 01:04:17,760
Speaker 1: what do you think people are overrating versus underrating in

1182
01:04:17,800 --> 01:04:19,280
Speaker 1: what was impactful in that race?

1183
01:04:21,680 --> 01:04:29,000
Speaker 3: I am very bullish on media savvy populists like I

1184
01:04:29,160 --> 01:04:32,959
Speaker 3: just right or left doesn't matter. I think people who

1185
01:04:33,160 --> 01:04:37,840
Speaker 3: understand how to communicate in the year twenty twenty five,

1186
01:04:38,240 --> 01:04:42,680
Speaker 3: who are really good at it, and who are willing

1187
01:04:42,760 --> 01:04:48,240
Speaker 3: to go and do things that don't feel so classically political,

1188
01:04:48,640 --> 01:04:50,720
Speaker 3: like the future is theirs.

1189
01:04:50,400 --> 01:04:52,560
Speaker 1: Not a stage, you know, not let you know that

1190
01:04:52,680 --> 01:04:53,720
Speaker 1: anything that looks.

1191
01:04:53,480 --> 01:04:55,960
Speaker 2: Like it's a cookie cutter.

1192
01:04:55,960 --> 01:04:57,440
Speaker 1: Or like yeah, you're supposed to do.

1193
01:04:57,520 --> 01:05:00,880
Speaker 3: There was a video making the realms of mom Donnie

1194
01:05:00,960 --> 01:05:04,560
Speaker 3: going to Halal Carts and being like make alall was

1195
01:05:04,600 --> 01:05:05,439
Speaker 3: it ten bucks again?

1196
01:05:05,560 --> 01:05:08,920
Speaker 2: Or make it eight bucks again? That like it was,

1197
01:05:09,200 --> 01:05:09,760
Speaker 2: It was great.

1198
01:05:09,840 --> 01:05:12,080
Speaker 3: It was like produced very It felt like it could

1199
01:05:12,080 --> 01:05:14,360
Speaker 3: have been produced by somebody doing like Man on the

1200
01:05:14,360 --> 01:05:16,400
Speaker 3: Street interviews for one of the late night comedy shows

1201
01:05:16,480 --> 01:05:19,200
Speaker 3: or something like that, Like it was entertaining to watch.

1202
01:05:19,840 --> 01:05:23,040
Speaker 3: I think if you are not entertaining, you are losing

1203
01:05:23,280 --> 01:05:26,000
Speaker 3: byballs in this media ecosystem.

1204
01:05:26,280 --> 01:05:28,840
Speaker 2: I think Donald everything that entertainment is what you're saying

1205
01:05:28,920 --> 01:05:29,440
Speaker 2: we are.

1206
01:05:30,320 --> 01:05:32,280
Speaker 3: And I'm not saying that as like an indictment of

1207
01:05:32,320 --> 01:05:36,120
Speaker 3: the American voter. I think it's it's completely rational for

1208
01:05:36,160 --> 01:05:39,280
Speaker 3: people to be drawn to things that engage, that make

1209
01:05:39,320 --> 01:05:41,880
Speaker 3: them feel, that make them laugh, that make them cry.

1210
01:05:41,960 --> 01:05:45,760
Speaker 3: That that's human nature. That's it's not just voters being dumb,

1211
01:05:45,800 --> 01:05:47,360
Speaker 3: like oh, I wish we could just make them all

1212
01:05:47,400 --> 01:05:49,640
Speaker 3: read you know, the Economist every week, like no, no,

1213
01:05:50,200 --> 01:05:53,080
Speaker 3: let's be realistic here. Content like that is really good.

1214
01:05:53,720 --> 01:05:56,600
Speaker 3: I have I have always been bullish on AOC for

1215
01:05:56,640 --> 01:05:58,800
Speaker 3: this very reason. I think she's excellent at this. I

1216
01:05:58,800 --> 01:06:01,840
Speaker 3: think her in her kitchen cooking while she's doing Instagram

1217
01:06:01,880 --> 01:06:04,200
Speaker 3: Lives looks great, and not everyone does a.

1218
01:06:04,400 --> 01:06:07,120
Speaker 2: Video game in Twitch too, like you know, Yes, I

1219
01:06:07,480 --> 01:06:10,560
Speaker 2: think she's playing chess while everybody else is playing checkers.

1220
01:06:10,760 --> 01:06:12,560
Speaker 1: She's a five star political athlete.

1221
01:06:12,640 --> 01:06:12,840
Speaker 2: You know.

1222
01:06:12,920 --> 01:06:15,600
Speaker 1: I'm a college football fan in the Star system, therefore

1223
01:06:15,600 --> 01:06:16,439
Speaker 1: a star five star.

1224
01:06:16,640 --> 01:06:17,400
Speaker 2: She's a five star.

1225
01:06:17,640 --> 01:06:19,520
Speaker 1: Now. I don't know if you win a national title

1226
01:06:19,520 --> 01:06:23,320
Speaker 1: with her, okay, but I know she's probably going to

1227
01:06:23,320 --> 01:06:25,560
Speaker 1: be the most talented candidate running for president if she

1228
01:06:25,640 --> 01:06:28,200
Speaker 1: chooses to run. Doesn't mean she wins the nomination and

1229
01:06:28,240 --> 01:06:31,880
Speaker 1: doesn't mean she becomes president, but that still, I would argue,

1230
01:06:31,880 --> 01:06:34,840
Speaker 1: makes it still would mean she's probably the most talented

1231
01:06:35,000 --> 01:06:37,880
Speaker 1: political athlete that'll be running.

1232
01:06:38,880 --> 01:06:39,520
Speaker 2: Yes, And so.

1233
01:06:39,520 --> 01:06:43,000
Speaker 3: I think to the extent that anybody is learning lessons

1234
01:06:43,040 --> 01:06:46,320
Speaker 3: from this, To me, it is less that voters are

1235
01:06:46,400 --> 01:06:49,960
Speaker 3: strongly ideological in one direction or another, but more that

1236
01:06:50,000 --> 01:06:53,480
Speaker 3: they will allow you to go ideological places they are not,

1237
01:06:54,200 --> 01:06:57,360
Speaker 3: so long as they feel like you actually care, that

1238
01:06:57,440 --> 01:06:59,840
Speaker 3: you actually give a damn, and that you're actually listening

1239
01:06:59,840 --> 01:07:02,480
Speaker 3: to someone like them, and the fact that you are

1240
01:07:02,640 --> 01:07:06,800
Speaker 3: creating content or messaging or the way you're speaking is

1241
01:07:06,840 --> 01:07:09,360
Speaker 3: not so far removed.

1242
01:07:08,960 --> 01:07:11,400
Speaker 2: From them, is in and of itself a signal that

1243
01:07:11,440 --> 01:07:12,280
Speaker 2: you care about them.

1244
01:07:12,640 --> 01:07:15,080
Speaker 3: And I mean to the extent that then somebody like

1245
01:07:15,080 --> 01:07:18,280
Speaker 3: a Puomo comes along so deeply flawed and comes in

1246
01:07:18,320 --> 01:07:20,959
Speaker 3: with a sense of entitlement like, oh, yes, of course

1247
01:07:21,000 --> 01:07:22,960
Speaker 3: I was going to win this. And how many times

1248
01:07:22,960 --> 01:07:25,480
Speaker 3: have we seen this where somebody is feels entitled to

1249
01:07:25,560 --> 01:07:29,680
Speaker 3: a race and therefore completely misses the challenge that's coming

1250
01:07:29,680 --> 01:07:30,040
Speaker 3: to them.

1251
01:07:30,120 --> 01:07:31,720
Speaker 2: This is a tale as oldest time.

1252
01:07:32,080 --> 01:07:35,600
Speaker 1: The very first race I covered semi professionally, Dick Thornberg.

1253
01:07:36,920 --> 01:07:40,720
Speaker 1: It was a Pennsylvania Senate race, Harris Wafford, Dick Thornberg.

1254
01:07:40,800 --> 01:07:44,080
Speaker 1: Dick Thornberg was George H. W. Bush's attorney general. They

1255
01:07:44,120 --> 01:07:46,880
Speaker 1: recruit him to be the nominee after John Hines dies

1256
01:07:47,720 --> 01:07:49,360
Speaker 1: and they knew they were going to have the special election.

1257
01:07:49,960 --> 01:07:52,800
Speaker 1: And he's up thirty points in the first poll. Sound familiar.

1258
01:07:52,880 --> 01:07:55,080
Speaker 2: Andrew Cuomo was up what thirty or forty points in

1259
01:07:55,120 --> 01:07:55,760
Speaker 2: the first poll.

1260
01:07:57,280 --> 01:08:02,880
Speaker 1: This sort of this college president literally with the patches

1261
01:08:02,920 --> 01:08:05,800
Speaker 1: on his elbows, that guy's not going anywhere. Sure enough,

1262
01:08:05,800 --> 01:08:08,600
Speaker 1: Harris Wafford becomes a Senator. The guys who work on

1263
01:08:08,640 --> 01:08:11,800
Speaker 1: Harris Wafford's campaign get hired by Bill Clinton. Those guys

1264
01:08:11,880 --> 01:08:16,599
Speaker 1: were guys named Jim Carvell and Paul mccallis. So when

1265
01:08:16,640 --> 01:08:20,360
Speaker 1: you say it's as old, literally, you see this, and

1266
01:08:22,080 --> 01:08:25,120
Speaker 1: there's always a point where a party sort of starts

1267
01:08:25,120 --> 01:08:27,960
Speaker 1: to atrophy because they've been in power too long. Right,

1268
01:08:28,080 --> 01:08:30,200
Speaker 1: that was we were getting on the you know, twelve

1269
01:08:30,280 --> 01:08:34,120
Speaker 1: years of Republican presidencies and all of that. So you

1270
01:08:34,160 --> 01:08:37,880
Speaker 1: could feel the And that's the one question I have

1271
01:08:38,000 --> 01:08:40,760
Speaker 1: to you, which is another question I have, which is

1272
01:08:40,800 --> 01:08:44,880
Speaker 1: about where we are in that. Do you think we

1273
01:08:45,320 --> 01:08:48,040
Speaker 1: twenty twenty four was a vote for an election or

1274
01:08:48,080 --> 01:08:51,000
Speaker 1: was it a vote against election? Meaning that last group

1275
01:08:51,040 --> 01:08:54,639
Speaker 1: of voters that made the decision, were they voting for

1276
01:08:54,760 --> 01:08:58,360
Speaker 1: Trump or were they voting against the Democrats.

1277
01:08:58,920 --> 01:09:04,479
Speaker 3: So I believe the polls suggested most Trump voters were

1278
01:09:04,560 --> 01:09:08,400
Speaker 3: voting for Trump and that most Harris voters were voting

1279
01:09:08,600 --> 01:09:12,360
Speaker 3: against Trump. Like that this really did to the extent

1280
01:09:12,400 --> 01:09:14,680
Speaker 3: that this was a referendum on Trump, like they kind

1281
01:09:14,680 --> 01:09:17,639
Speaker 3: of succeeded in making it a referendum on Trump.

1282
01:09:17,640 --> 01:09:19,479
Speaker 2: That just didn't menuh, think it was more.

1283
01:09:19,439 --> 01:09:21,200
Speaker 1: Of a referendum on Trump and not on Biden.

1284
01:09:24,240 --> 01:09:25,800
Speaker 2: I suppose for.

1285
01:09:28,720 --> 01:09:30,840
Speaker 3: That's a good point, and I guess the question doesn't

1286
01:09:30,840 --> 01:09:33,040
Speaker 3: allow for the possibility that Biden was a factor. Right,

1287
01:09:33,080 --> 01:09:35,719
Speaker 3: It's either you know, was it for Trump or against Harris?

1288
01:09:35,760 --> 01:09:38,280
Speaker 3: And Biden's not listed in that question. I mean, I

1289
01:09:38,280 --> 01:09:40,680
Speaker 3: definitely think that the Biden of it all, and the

1290
01:09:40,720 --> 01:09:42,760
Speaker 3: fact that we gave him a chance to govern, we

1291
01:09:42,800 --> 01:09:45,320
Speaker 3: gave him a chance to undo the chaos and the mayhem,

1292
01:09:45,360 --> 01:09:47,479
Speaker 3: and instead the control room was left empty, and so like,

1293
01:09:47,520 --> 01:09:50,559
Speaker 3: I'm sure that was a massive factor here. But I

1294
01:09:50,600 --> 01:09:54,320
Speaker 3: just think it's interesting most Trump voters report not going

1295
01:09:54,360 --> 01:09:56,040
Speaker 3: to the polls to be like, well, I don't really

1296
01:09:56,080 --> 01:09:58,719
Speaker 3: like this guy, but gosh, can you imagine Kamala Harris?

1297
01:09:58,880 --> 01:10:01,320
Speaker 2: That was a piece said he's a voter base. But

1298
01:10:01,920 --> 01:10:05,360
Speaker 2: you know, something like fifties, maybe almost sixty percent of

1299
01:10:05,360 --> 01:10:07,040
Speaker 2: Trump voters. I'll have to look this back up.

1300
01:10:07,040 --> 01:10:09,960
Speaker 3: I hate that knowing the exact number said the vote

1301
01:10:10,000 --> 01:10:15,639
Speaker 3: was mostly for Trump. Let me throw one other thing

1302
01:10:15,640 --> 01:10:18,000
Speaker 3: in there, Yeah, it could if you want to make

1303
01:10:18,040 --> 01:10:21,280
Speaker 3: the argument this was an election against just against the

1304
01:10:21,320 --> 01:10:22,080
Speaker 3: status quo.

1305
01:10:23,200 --> 01:10:25,639
Speaker 1: Right, Well, that's what the voters keep doing when given

1306
01:10:25,680 --> 01:10:30,160
Speaker 1: a choice between continuation or trying a new direction, even

1307
01:10:30,200 --> 01:10:33,920
Speaker 1: if it's a previous direction every time, but twice this

1308
01:10:34,160 --> 01:10:39,479
Speaker 1: century they've chosen a new direction. And I don't do

1309
01:10:39,560 --> 01:10:41,760
Speaker 1: you see any evidence that that's going to change in

1310
01:10:41,800 --> 01:10:42,840
Speaker 1: twenty six or twenty eight.

1311
01:10:42,880 --> 01:10:48,439
Speaker 3: Yet no, And that's why things that today sound completely insane,

1312
01:10:48,680 --> 01:10:52,160
Speaker 3: like Gavin Newsom being the Democratic nominee who then goes

1313
01:10:52,160 --> 01:10:54,400
Speaker 3: on to become president. Like, I don't dismiss those things

1314
01:10:54,400 --> 01:10:56,840
Speaker 3: that sound completely insane, because you know what would have

1315
01:10:56,880 --> 01:10:59,680
Speaker 3: sounded insane in twenty twenty or two thousand and four,

1316
01:10:59,680 --> 01:11:03,400
Speaker 3: Wards or Wish was re elected that a gentleman from

1317
01:11:03,400 --> 01:11:06,120
Speaker 3: Illinois named Barack Hussein Obama would be his successor, Like

1318
01:11:06,160 --> 01:11:06,599
Speaker 3: that would have.

1319
01:11:06,560 --> 01:11:10,479
Speaker 2: Sounded Iraq War era. That would have sounded insane, And

1320
01:11:10,560 --> 01:11:11,280
Speaker 2: yet it happened.

1321
01:11:11,439 --> 01:11:13,360
Speaker 3: And then if you would have said, you know what,

1322
01:11:13,400 --> 01:11:17,280
Speaker 3: who's going to follow Barack Obama as president Donald freaking Trump, people,

1323
01:11:17,360 --> 01:11:18,320
Speaker 3: is that you're insane?

1324
01:11:19,080 --> 01:11:21,479
Speaker 2: And then it happened, And so like, what.

1325
01:11:21,400 --> 01:11:24,960
Speaker 3: Is the next what is the next most insane possibility?

1326
01:11:26,240 --> 01:11:28,240
Speaker 2: I'll give that at least a ten percent chance of happening.

1327
01:11:35,479 --> 01:11:39,920
Speaker 1: Do you consider the electorate, where's the electorate stable and

1328
01:11:39,960 --> 01:11:40,960
Speaker 1: where's it unstable?

1329
01:11:43,680 --> 01:11:48,960
Speaker 3: I think the electorate is pretty stable with regards to

1330
01:11:49,600 --> 01:11:52,639
Speaker 3: highly educated voters. I think Democrats own them and own

1331
01:11:52,680 --> 01:11:58,759
Speaker 3: them for a long time. I think the working class

1332
01:11:59,479 --> 01:12:03,080
Speaker 3: is up for grabs and will entirely hinge on how

1333
01:12:03,120 --> 01:12:04,160
Speaker 3: the economy is doing.

1334
01:12:05,360 --> 01:12:08,479
Speaker 2: Really, we have a poll finding recently that are more

1335
01:12:08,560 --> 01:12:11,080
Speaker 2: up for grabs than maybe some people realize.

1336
01:12:12,479 --> 01:12:14,439
Speaker 3: I think it all depends on is does Trump do

1337
01:12:14,520 --> 01:12:16,760
Speaker 3: with the economy what he promised or not. We had

1338
01:12:16,800 --> 01:12:19,240
Speaker 3: a pull finding recently. We had asked a bunch of

1339
01:12:19,280 --> 01:12:23,240
Speaker 3: different questions about whether you supported or opposed tariffs on

1340
01:12:23,360 --> 01:12:28,920
Speaker 3: a wide range of different goods and services, and we

1341
01:12:28,920 --> 01:12:31,600
Speaker 3: were looking at the Republican respondents and then breaking it

1342
01:12:31,600 --> 01:12:35,600
Speaker 3: out by college versus non college And I think the

1343
01:12:35,760 --> 01:12:39,280
Speaker 3: discourse around tariffs makes you think that it is non

1344
01:12:39,360 --> 01:12:42,880
Speaker 3: college educated Republicans, these like working class Republicans, that they're

1345
01:12:42,880 --> 01:12:45,120
Speaker 3: the ones that are demanding that Donald Trump do something

1346
01:12:45,160 --> 01:12:47,240
Speaker 3: about a trade system that has been screwing the little

1347
01:12:47,240 --> 01:12:50,320
Speaker 3: guy for whatever. And yet they were the ones that

1348
01:12:50,360 --> 01:12:53,040
Speaker 3: were the most were the least excited about a whole

1349
01:12:53,120 --> 01:12:55,400
Speaker 3: range of tariffs. And I was like, I went to

1350
01:12:55,439 --> 01:12:56,719
Speaker 3: my team, I was like, can we have to double

1351
01:12:56,800 --> 01:12:58,479
Speaker 3: check and make sure that this is not like a

1352
01:12:58,520 --> 01:13:01,040
Speaker 3: coding error in the crosstubs or something, And they're like no.

1353
01:13:02,040 --> 01:13:04,920
Speaker 3: And ultimately what we then subsequently found out through other research,

1354
01:13:04,960 --> 01:13:06,600
Speaker 3: I mean that those are the folks who are the

1355
01:13:06,640 --> 01:13:08,880
Speaker 3: most hurt when the price of something at the store

1356
01:13:08,920 --> 01:13:12,240
Speaker 3: goes up five percent, They're not the ones. So this

1357
01:13:12,360 --> 01:13:15,000
Speaker 3: whole concept of like the working class and what drives them,

1358
01:13:15,040 --> 01:13:17,719
Speaker 3: I think this cost of living question is so massive.

1359
01:13:17,960 --> 01:13:19,439
Speaker 3: I think it's a huge piece of what happened in

1360
01:13:19,479 --> 01:13:22,000
Speaker 3: New York and I think if there is failure on

1361
01:13:22,040 --> 01:13:24,360
Speaker 3: that front for Trump, a lot of those voters would

1362
01:13:24,360 --> 01:13:26,280
Speaker 3: be up for grabs again to the Democrats.

1363
01:13:26,520 --> 01:13:29,800
Speaker 1: One of my favorite barometer questions that Bill McInturff and

1364
01:13:29,800 --> 01:13:33,800
Speaker 1: I are both obsessed with is the question about should

1365
01:13:33,840 --> 01:13:36,200
Speaker 1: government do more or should government do less. We think

1366
01:13:36,200 --> 01:13:38,519
Speaker 1: it's as good of a question to ask as direction

1367
01:13:38,600 --> 01:13:40,960
Speaker 1: of the country, because in many ways you sort of

1368
01:13:40,960 --> 01:13:43,960
Speaker 1: see it. And there's been a general pattern over the

1369
01:13:44,040 --> 01:13:47,640
Speaker 1: last we've been over a twenty year period, which is,

1370
01:13:47,960 --> 01:13:51,080
Speaker 1: when Democrats are in power, a slight majority believe government's

1371
01:13:51,080 --> 01:13:53,880
Speaker 1: doing too much, and when Republicans are in power, a

1372
01:13:53,880 --> 01:13:57,479
Speaker 1: slight majority believe government should do more. This most recent

1373
01:13:57,520 --> 01:14:01,679
Speaker 1: CY and N filing had fifty eight saying government should

1374
01:14:01,680 --> 01:14:06,760
Speaker 1: do more. I assumed some of that was Medicaid backlash,

1375
01:14:07,080 --> 01:14:11,560
Speaker 1: but I also wonder if Trump has changed the perception

1376
01:14:11,920 --> 01:14:16,120
Speaker 1: of what government should do with Republicans themselves. And so therefore,

1377
01:14:16,120 --> 01:14:19,639
Speaker 1: while Independents and Democrats are sort of responding the same

1378
01:14:19,640 --> 01:14:22,040
Speaker 1: way they've been responding for twenty years on the question

1379
01:14:22,800 --> 01:14:26,519
Speaker 1: that actually you now have that Donald Trump has changed

1380
01:14:26,520 --> 01:14:30,439
Speaker 1: the Republican electorate and Republican expectations that hey, no, no, no, no, no,

1381
01:14:30,439 --> 01:14:33,759
Speaker 1: small government isn't necessarily a good thing. You want strong

1382
01:14:33,800 --> 01:14:36,679
Speaker 1: government and there are parts of government that you want

1383
01:14:36,720 --> 01:14:41,760
Speaker 1: to work in your benefit. Have you been able to

1384
01:14:41,840 --> 01:14:45,200
Speaker 1: see more evidence of that that a rank and file

1385
01:14:45,240 --> 01:14:51,280
Speaker 1: Republican actually wants government? Yes, twenty years ago.

1386
01:14:51,479 --> 01:14:52,759
Speaker 2: Yes.

1387
01:14:53,040 --> 01:14:55,840
Speaker 3: And there are two things going on here. First, is

1388
01:14:56,720 --> 01:14:59,360
Speaker 3: this belief. So the way that we've asked it in

1389
01:14:59,600 --> 01:15:02,479
Speaker 3: our sha Un polling is it's not as elegant as yours,

1390
01:15:02,840 --> 01:15:04,880
Speaker 3: but ours is which one do you agree with more?

1391
01:15:04,920 --> 01:15:08,760
Speaker 3: It is preferable to have bigger government providing more services

1392
01:15:08,880 --> 01:15:12,559
Speaker 3: or smaller government providing fewer services. And when we ask

1393
01:15:12,640 --> 01:15:16,080
Speaker 3: it that way, we still find among Republicans a sizable

1394
01:15:16,080 --> 01:15:19,800
Speaker 3: majority say smaller government providing fewer services. But if you

1395
01:15:19,840 --> 01:15:23,880
Speaker 3: look at just Republicans under fifty, they're actually more likely

1396
01:15:23,960 --> 01:15:29,840
Speaker 3: to want that robust role for government. They're not as

1397
01:15:29,920 --> 01:15:33,960
Speaker 3: much here in the GOP for like the old libertarian

1398
01:15:34,240 --> 01:15:38,439
Speaker 3: liberted government type reasons, which I think is interesting. The

1399
01:15:38,520 --> 01:15:40,840
Speaker 3: other thing that we've asked is a question where we

1400
01:15:40,880 --> 01:15:42,600
Speaker 3: all and we only ask this of the Republicans in

1401
01:15:42,640 --> 01:15:44,559
Speaker 3: our survey, but we ask which one do you agree with?

1402
01:15:44,600 --> 01:15:47,600
Speaker 3: More businesses should be able to operate however they like,

1403
01:15:47,680 --> 01:15:50,040
Speaker 3: as long as they do not break the law, versus

1404
01:15:50,439 --> 01:15:53,640
Speaker 3: businesses should be held accountable if they are too focused.

1405
01:15:53,320 --> 01:15:54,519
Speaker 2: On being woke.

1406
01:15:55,240 --> 01:15:57,240
Speaker 3: So this is the like, when is it appropriate to

1407
01:15:57,320 --> 01:16:00,000
Speaker 3: use the power of the state to come after private business,

1408
01:16:00,080 --> 01:16:00,479
Speaker 3: which is.

1409
01:16:00,439 --> 01:16:03,719
Speaker 2: Something during the Romney Job creators are great?

1410
01:16:03,920 --> 01:16:05,880
Speaker 3: Get government out of the way of business like would

1411
01:16:05,920 --> 01:16:09,720
Speaker 3: have been unfathomable by a five point margin. Republicans lean

1412
01:16:09,760 --> 01:16:11,760
Speaker 3: toward that latter statement when we last asked it.

1413
01:16:12,120 --> 01:16:15,120
Speaker 1: That's the idea of life. Yeah, Ana Santas has been

1414
01:16:15,120 --> 01:16:18,639
Speaker 1: governing this way, probably more so than any other Republican governor,

1415
01:16:19,840 --> 01:16:22,080
Speaker 1: and I keep thinking it's going to backlash on them,

1416
01:16:22,080 --> 01:16:22,599
Speaker 1: and it hasn't.

1417
01:16:23,880 --> 01:16:29,200
Speaker 3: Now there are certain things where we still find In

1418
01:16:29,439 --> 01:16:32,360
Speaker 3: the same survey, we asked a question about, like, should

1419
01:16:32,400 --> 01:16:36,880
Speaker 3: companies be doing like the E and E SG, right

1420
01:16:37,320 --> 01:16:41,480
Speaker 3: ESG environmental social governments that's come under fire from Republicans.

1421
01:16:42,240 --> 01:16:44,880
Speaker 3: Actually it's the social and governance part that Republicans get

1422
01:16:44,880 --> 01:16:47,479
Speaker 3: really fired up about, but really not so mad about.

1423
01:16:47,520 --> 01:16:50,759
Speaker 3: A company that decides it wants to do green stuff

1424
01:16:51,040 --> 01:16:53,720
Speaker 3: or try to reduce less carbon like that. Actually, that

1425
01:16:53,720 --> 01:16:59,240
Speaker 3: one pulls completely differently than the like woke or they're social.

1426
01:16:58,960 --> 01:17:02,080
Speaker 1: Governments should have You just may have inadvertently sent a

1427
01:17:02,080 --> 01:17:06,599
Speaker 1: memo to environmental groups, Hey, don't linked arms with the

1428
01:17:06,640 --> 01:17:11,120
Speaker 1: rest of the progressive social network. If you separate out,

1429
01:17:11,200 --> 01:17:13,080
Speaker 1: you might have a better chance of selling your message.

1430
01:17:13,120 --> 01:17:15,639
Speaker 2: I mean, the polling among Republicans just looks completely different

1431
01:17:15,640 --> 01:17:17,520
Speaker 2: for those issues. That's fascinating.

1432
01:17:19,280 --> 01:17:21,160
Speaker 1: Let's talk a little bit about the state of polling,

1433
01:17:21,439 --> 01:17:24,040
Speaker 1: and I look at it more as methodology. Look, I

1434
01:17:24,080 --> 01:17:27,160
Speaker 1: actually think polling's pretty good because I'm not looking for

1435
01:17:27,240 --> 01:17:30,360
Speaker 1: it to be pinpoint accuracy. I'm a trend person. I

1436
01:17:30,360 --> 01:17:32,400
Speaker 1: look for trend line that's why I hate real clear

1437
01:17:32,400 --> 01:17:34,639
Speaker 1: politics and I hate Nate.

1438
01:17:34,479 --> 01:17:37,280
Speaker 2: Silver In what they do with combining data.

1439
01:17:37,320 --> 01:17:40,080
Speaker 1: I think combining data, I think you take good data

1440
01:17:40,120 --> 01:17:40,599
Speaker 1: and bad data.

1441
01:17:40,640 --> 01:17:41,680
Speaker 2: It makes it all bad.

1442
01:17:42,760 --> 01:17:46,720
Speaker 1: I understand why it's easier to report on polling by

1443
01:17:46,800 --> 01:17:49,840
Speaker 1: just averaging everything out, but I'm one of those who

1444
01:17:49,840 --> 01:17:53,400
Speaker 1: believes a filet Mignon and a pile of dog excrement

1445
01:17:53,560 --> 01:17:56,040
Speaker 1: is going to make everything taste like dog extrement. So

1446
01:17:56,280 --> 01:17:59,000
Speaker 1: I'm being very polite here, even though in a podcast world,

1447
01:17:59,040 --> 01:18:01,639
Speaker 1: right we can say what we want. So I kind

1448
01:18:01,640 --> 01:18:05,880
Speaker 1: of view the state of polling as generally, if you

1449
01:18:06,760 --> 01:18:08,840
Speaker 1: if you know, if you're good, if you're a good

1450
01:18:08,880 --> 01:18:11,200
Speaker 1: consumer of it. There's good stuff out there, but there's

1451
01:18:11,240 --> 01:18:13,519
Speaker 1: a lot of crap that's putting out there. But I

1452
01:18:13,520 --> 01:18:15,240
Speaker 1: think most of it is due to what kind of

1453
01:18:15,280 --> 01:18:19,160
Speaker 1: methodology you choose to use in your poll. So that

1454
01:18:19,320 --> 01:18:22,720
Speaker 1: is what I'm curious about. What is the best you

1455
01:18:22,800 --> 01:18:24,599
Speaker 1: got to do it? Twenty I'm going to say, first

1456
01:18:24,600 --> 01:18:27,519
Speaker 1: of all, if you want to do a nationwide sample

1457
01:18:27,680 --> 01:18:31,360
Speaker 1: that you're comfortable with, how many respondents do you want?

1458
01:18:31,360 --> 01:18:31,880
Speaker 2: These days?

1459
01:18:33,880 --> 01:18:36,000
Speaker 3: So we do a thousand, and I'm still okay with

1460
01:18:36,040 --> 01:18:40,839
Speaker 3: that because of the salon magic that we use.

1461
01:18:40,880 --> 01:18:43,280
Speaker 1: And having vot file and starting with using a voter file.

1462
01:18:43,400 --> 01:18:46,360
Speaker 2: Yes, that's to me. That's for anything that's going to

1463
01:18:46,400 --> 01:18:48,439
Speaker 2: be political, you have to do that.

1464
01:18:50,880 --> 01:18:53,679
Speaker 1: So that's just with a thousand. You're comfortable with a thousand.

1465
01:18:53,680 --> 01:18:56,080
Speaker 1: I only say that because that means you're only going

1466
01:18:56,160 --> 01:19:02,000
Speaker 1: to have at best, you know, one hundred and eighty latinos, right,

1467
01:19:02,400 --> 01:19:04,640
Speaker 1: And isn't I mean that that to me, it's the

1468
01:19:04,760 --> 01:19:08,000
Speaker 1: subsamples that become problematic if you want to look at them.

1469
01:19:08,080 --> 01:19:10,719
Speaker 3: Oh yeah, for sure, because then things get really noisy.

1470
01:19:10,760 --> 01:19:13,719
Speaker 3: And so what you can't do as much of is say,

1471
01:19:13,840 --> 01:19:16,840
Speaker 3: oh man, from months to months to month. Republicans under

1472
01:19:16,880 --> 01:19:20,120
Speaker 3: fifty have moved X, Y, and z because the margin

1473
01:19:20,120 --> 01:19:23,200
Speaker 3: of eraon that some sample is so massivest to make

1474
01:19:23,240 --> 01:19:24,000
Speaker 3: it unusable.

1475
01:19:24,040 --> 01:19:25,120
Speaker 2: So you're right.

1476
01:19:25,200 --> 01:19:26,960
Speaker 3: I mean, in an ideal world, I love to have

1477
01:19:26,960 --> 01:19:30,200
Speaker 3: two thousand, but I think just forgetting like a pulse

1478
01:19:30,200 --> 01:19:33,040
Speaker 3: of the country, I'm still okay with a thousand as

1479
01:19:33,040 --> 01:19:33,960
Speaker 3: long as I would.

1480
01:19:34,200 --> 01:19:35,639
Speaker 2: Let me put it this way, I'd rather.

1481
01:19:35,520 --> 01:19:39,080
Speaker 3: Have a thousand that is really well executed, that we

1482
01:19:39,160 --> 01:19:42,400
Speaker 3: have invested in, rather than just taken like the cheapest

1483
01:19:42,439 --> 01:19:43,600
Speaker 3: available sampling.

1484
01:19:43,479 --> 01:19:46,840
Speaker 1: Survey Monkey idea, which is they do nineteen thousand, right,

1485
01:19:46,920 --> 01:19:50,040
Speaker 1: but you know it's probably I'd much rather have.

1486
01:19:50,040 --> 01:19:54,800
Speaker 2: A thousand good interviews than two thousand questionable.

1487
01:19:55,160 --> 01:19:56,960
Speaker 1: And I'm not trying to make you pick on survey

1488
01:19:57,040 --> 01:19:59,320
Speaker 1: Monkey and I will le oh no, no, no, you

1489
01:19:59,360 --> 01:20:02,559
Speaker 1: know I I say this love I actually John Cones.

1490
01:20:02,760 --> 01:20:06,760
Speaker 1: I know he's a good statistician on there. I'm just

1491
01:20:06,840 --> 01:20:12,040
Speaker 1: not as I'm a little squarely on opt in surveys

1492
01:20:12,080 --> 01:20:15,519
Speaker 1: in general. I feel like opt in surveys can What

1493
01:20:15,640 --> 01:20:18,280
Speaker 1: I mean by that it was just you voluntarily, you know,

1494
01:20:18,760 --> 01:20:22,120
Speaker 1: conduct a survey, and I just think that that that

1495
01:20:22,400 --> 01:20:24,960
Speaker 1: has an inherent bias to it people that are willing

1496
01:20:25,000 --> 01:20:27,439
Speaker 1: to do so. Now, I guess anybody willing to do

1497
01:20:27,439 --> 01:20:30,080
Speaker 1: a survey, there's going to be some bias. But that's

1498
01:20:30,080 --> 01:20:31,800
Speaker 1: why I get a little nervous about that. All Right,

1499
01:20:31,840 --> 01:20:35,000
Speaker 1: So we've established you're if it's a good voter file

1500
01:20:35,080 --> 01:20:39,519
Speaker 1: driven sample, you're good with a thousand. Now, how do

1501
01:20:39,560 --> 01:20:42,799
Speaker 1: you contact those thousand? What's the best way to contact

1502
01:20:42,800 --> 01:20:43,240
Speaker 1: a thousand?

1503
01:20:43,360 --> 01:20:43,920
Speaker 2: And is there?

1504
01:20:44,439 --> 01:20:47,759
Speaker 1: Are you a mixed mode person meaning some phone, some text,

1505
01:20:47,800 --> 01:20:50,639
Speaker 1: some this, or is there one mode you can use

1506
01:20:50,680 --> 01:20:52,400
Speaker 1: to do it and still get a good sample.

1507
01:20:53,520 --> 01:20:58,320
Speaker 3: So I still think that you can use opt in

1508
01:20:58,760 --> 01:21:01,640
Speaker 3: as long as you do a lot of things to

1509
01:21:01,760 --> 01:21:05,400
Speaker 3: keep out the bots, the professional survey takers that you know.

1510
01:21:05,720 --> 01:21:08,479
Speaker 3: So we do things like we flag IP addresses that

1511
01:21:08,840 --> 01:21:11,520
Speaker 3: you know, or if we flag when somebody's using APPN,

1512
01:21:11,600 --> 01:21:13,320
Speaker 3: it doesn't mean I think they're always excluded, but we

1513
01:21:13,479 --> 01:21:16,000
Speaker 3: then at just their like interview comes in, they're more stard.

1514
01:21:16,040 --> 01:21:18,040
Speaker 1: Verify it's a VPN right that you know for sure

1515
01:21:18,040 --> 01:21:20,080
Speaker 1: what geolocation they're at, right, right?

1516
01:21:20,800 --> 01:21:24,040
Speaker 3: We Uh, there's a there's a question that PEW I

1517
01:21:24,080 --> 01:21:26,400
Speaker 3: think added to some of their surveys that we've started at,

1518
01:21:26,680 --> 01:21:31,600
Speaker 3: which is are you certified to operate something class submarine?

1519
01:21:31,640 --> 01:21:33,760
Speaker 3: And like if you answer yes, you are removed from

1520
01:21:33,800 --> 01:21:37,519
Speaker 3: the survey because there's like twenty people on earth. So sorry,

1521
01:21:37,560 --> 01:21:39,920
Speaker 3: our sample is biased against submarine captives.

1522
01:21:39,960 --> 01:21:41,640
Speaker 2: But is it a way to find out if you

1523
01:21:41,640 --> 01:21:42,759
Speaker 2: have a liar in your survey?

1524
01:21:42,880 --> 01:21:43,519
Speaker 1: Is that the idea?

1525
01:21:43,640 --> 01:21:44,360
Speaker 2: Yeah, Well, it's.

1526
01:21:44,200 --> 01:21:47,120
Speaker 3: Either either a liar or someone who's just not paying

1527
01:21:47,160 --> 01:21:50,200
Speaker 3: attention and they're just like clicking yes to everything, which

1528
01:21:50,240 --> 01:21:52,200
Speaker 3: we can also do because we look at the average

1529
01:21:52,280 --> 01:21:54,559
Speaker 3: length of time people take to take the survey, and

1530
01:21:54,600 --> 01:21:56,960
Speaker 3: we can lop off the interviews that are at the

1531
01:21:57,240 --> 01:21:58,439
Speaker 3: fastest end of that.

1532
01:22:00,240 --> 01:22:00,920
Speaker 2: Open ends.

1533
01:22:00,960 --> 01:22:03,000
Speaker 3: And most of the time when we're asking open ends

1534
01:22:03,000 --> 01:22:04,920
Speaker 3: now it's not because I just want the data. I mean,

1535
01:22:04,960 --> 01:22:07,080
Speaker 3: I love a good open end, but it's also you

1536
01:22:07,120 --> 01:22:10,160
Speaker 3: can very clearly find going through that the people who

1537
01:22:10,200 --> 01:22:14,160
Speaker 3: are like just putting nonsense in to just like get

1538
01:22:14,200 --> 01:22:15,960
Speaker 3: through the survey to get their discard or whatever.

1539
01:22:16,680 --> 01:22:18,200
Speaker 2: So we do all of those things.

1540
01:22:18,640 --> 01:22:22,240
Speaker 3: The thing that's scary so we Every summer there's a

1541
01:22:22,280 --> 01:22:24,840
Speaker 3: conference called Aport. It's all the polsters come together and

1542
01:22:24,840 --> 01:22:27,000
Speaker 3: they all panic about all the things that are wrong

1543
01:22:27,000 --> 01:22:29,160
Speaker 3: in our industry. And this year the big panic is

1544
01:22:29,240 --> 01:22:30,639
Speaker 3: generative AI and what it's going.

1545
01:22:30,560 --> 01:22:31,439
Speaker 2: To mean for our industry.

1546
01:22:31,439 --> 01:22:33,479
Speaker 3: Because right now there are lots of ways I can

1547
01:22:33,560 --> 01:22:35,639
Speaker 3: use these tools to help me analyze a data set.

1548
01:22:36,600 --> 01:22:39,080
Speaker 3: But the bots are coming and they're getting better. The

1549
01:22:39,120 --> 01:22:41,320
Speaker 3: bots are going to learn stop checking yes to the

1550
01:22:41,360 --> 01:22:42,240
Speaker 3: submarine question.

1551
01:22:42,439 --> 01:22:43,320
Speaker 2: The bots are going to.

1552
01:22:43,320 --> 01:22:48,720
Speaker 1: Learn are nervous that we could have surveys totally essentially

1553
01:22:49,960 --> 01:22:55,840
Speaker 1: poisoned by people with a AI army of survey box.

1554
01:22:57,560 --> 01:23:00,599
Speaker 3: And this was I made a joke on Twitter this

1555
01:23:00,600 --> 01:23:03,479
Speaker 3: past week because an article came out in the Atlantic

1556
01:23:03,520 --> 01:23:06,600
Speaker 3: that kids are starting to get landline phones again, that

1557
01:23:06,720 --> 01:23:08,240
Speaker 3: like parents who don't want to give their kids a

1558
01:23:08,240 --> 01:23:10,559
Speaker 3: smartphone are putting a landline in their room. And I

1559
01:23:10,600 --> 01:23:12,280
Speaker 3: was like, it's like in The Lord of the Rings,

1560
01:23:12,320 --> 01:23:16,120
Speaker 3: like when Geddolph comes back and they're like, you're back.

1561
01:23:16,200 --> 01:23:18,840
Speaker 3: You're here to help us fight the AI orcs that

1562
01:23:18,920 --> 01:23:19,880
Speaker 3: are coming for us.

1563
01:23:20,160 --> 01:23:22,160
Speaker 2: Than welcome back to the battle.

1564
01:23:22,800 --> 01:23:25,800
Speaker 1: Don't forget ben Laden didn't use the cellphone for a reason, right,

1565
01:23:25,960 --> 01:23:29,920
Speaker 1: Like he was using old fashioned couriers and passing pieces

1566
01:23:29,920 --> 01:23:34,439
Speaker 1: of paper. I mean, it is a it is. You know,

1567
01:23:35,160 --> 01:23:39,720
Speaker 1: the more wired we become, the more old technologies are

1568
01:23:39,760 --> 01:23:40,639
Speaker 1: going to be secure.

1569
01:23:41,320 --> 01:23:44,160
Speaker 3: Yeah, and so there's always this pushing pull with new technology.

1570
01:23:44,320 --> 01:23:46,439
Speaker 3: It makes it easier for me as a polster to

1571
01:23:46,720 --> 01:23:48,880
Speaker 3: find you, and it makes it easier for you as

1572
01:23:48,880 --> 01:23:50,280
Speaker 3: a respondent to evade me and.

1573
01:23:50,360 --> 01:23:50,720
Speaker 2: Live to me.

1574
01:23:50,840 --> 01:23:53,519
Speaker 3: And so there's always that push and pull. And I

1575
01:23:53,560 --> 01:23:57,639
Speaker 3: guess the worry is then when you have generative AI

1576
01:23:58,080 --> 01:24:01,520
Speaker 3: taking over as the responder, what are the consequences?

1577
01:24:01,560 --> 01:24:01,760
Speaker 2: Then.

1578
01:24:02,600 --> 01:24:05,519
Speaker 3: One of the things that's really fought in the industry

1579
01:24:05,560 --> 01:24:08,479
Speaker 3: these days is like a synthetic population that you basically

1580
01:24:08,640 --> 01:24:11,320
Speaker 3: use AI to say, generate for me a data set

1581
01:24:11,360 --> 01:24:13,720
Speaker 3: of what a thousand New York City voters would be

1582
01:24:14,520 --> 01:24:16,439
Speaker 3: and they can kind of do it. What I don't

1583
01:24:16,479 --> 01:24:18,400
Speaker 3: love about it is like, what is your training data?

1584
01:24:18,479 --> 01:24:20,719
Speaker 3: Is your training data a poll? Then just do the poll?

1585
01:24:20,880 --> 01:24:23,280
Speaker 3: Like why are we doing a poll to train the data?

1586
01:24:23,400 --> 01:24:26,680
Speaker 1: St York City polling off because it was yes, they

1587
01:24:26,680 --> 01:24:31,040
Speaker 1: were using the twenty twenty one electorate and it turned

1588
01:24:31,040 --> 01:24:33,760
Speaker 1: out the twenty twenty one electorate was radically different than

1589
01:24:33,760 --> 01:24:34,799
Speaker 1: the twenty twenty five elector.

1590
01:24:35,520 --> 01:24:36,479
Speaker 2: Yeah, that was.

1591
01:24:38,000 --> 01:24:41,840
Speaker 3: I mean, I pulling an RCV race is hard, but

1592
01:24:41,920 --> 01:24:44,000
Speaker 3: it like the first round was just so off on

1593
01:24:44,040 --> 01:24:48,080
Speaker 3: so many of those polls.

1594
01:24:46,479 --> 01:24:47,360
Speaker 2: Just methodologically.

1595
01:24:47,600 --> 01:24:50,280
Speaker 3: The message that my research joanalyst too went to Aport

1596
01:24:50,280 --> 01:24:52,080
Speaker 3: came back with was like, when it comes to AI,

1597
01:24:52,920 --> 01:24:55,200
Speaker 3: this is like what they used to say about It's

1598
01:24:55,200 --> 01:24:56,680
Speaker 3: like if you encounter a bear in the woods, Like

1599
01:24:56,680 --> 01:24:58,040
Speaker 3: you don't have to outrun the bear, You just have

1600
01:24:58,080 --> 01:25:01,800
Speaker 3: to outrun the people you're with. Just make your survey

1601
01:25:01,840 --> 01:25:05,160
Speaker 3: better than your competitors, and the AI bots will flood

1602
01:25:05,160 --> 01:25:07,720
Speaker 3: to your competitors survey if you make the barrier for

1603
01:25:07,800 --> 01:25:10,240
Speaker 3: them to complete yours high enough like they won't bother

1604
01:25:11,000 --> 01:25:14,760
Speaker 3: So you just have to make your survey extra air

1605
01:25:14,800 --> 01:25:16,840
Speaker 3: type so that the bots go elsewhere because it's not

1606
01:25:16,840 --> 01:25:18,559
Speaker 3: worth it to try to solve your survey.

1607
01:25:19,000 --> 01:25:21,439
Speaker 1: Do you get any Do you feel like you get

1608
01:25:21,439 --> 01:25:24,880
Speaker 1: any insight by averaging of puls that are of different

1609
01:25:24,880 --> 01:25:27,519
Speaker 1: methodologies in different or do you think it can be misleading?

1610
01:25:29,479 --> 01:25:33,679
Speaker 3: I don't mind it. I do appreciate when polsters try

1611
01:25:33,720 --> 01:25:37,519
Speaker 3: to wait polls on the basis of past accuracy, So

1612
01:25:38,920 --> 01:25:41,200
Speaker 3: taking something that in the past has not had a

1613
01:25:41,200 --> 01:25:43,120
Speaker 3: good track record and saying we're only going to count

1614
01:25:43,160 --> 01:25:45,920
Speaker 3: this x percentage, you know, I think that makes it

1615
01:25:46,000 --> 01:25:49,120
Speaker 3: a little bit better. What I also like about it

1616
01:25:49,200 --> 01:25:52,599
Speaker 3: is that typically those averages don't pingpong around as much,

1617
01:25:53,000 --> 01:25:54,559
Speaker 3: like something that always drives me crazy.

1618
01:25:54,560 --> 01:25:55,599
Speaker 2: And I'm I assume this.

1619
01:25:55,560 --> 01:25:57,599
Speaker 1: May have you worry that you're going to miss You're

1620
01:25:57,600 --> 01:26:00,160
Speaker 1: going to miss something, you know. I always worry that

1621
01:26:00,200 --> 01:26:03,439
Speaker 1: if you if you level everything out, then you may

1622
01:26:03,600 --> 01:26:08,080
Speaker 1: miss something because you've averaged out an outlier that actually

1623
01:26:09,080 --> 01:26:10,439
Speaker 1: was going to provide insight to an all.

1624
01:26:10,520 --> 01:26:12,679
Speaker 3: I think I wouldn't be moving, I wouldn't use only

1625
01:26:12,720 --> 01:26:16,200
Speaker 3: the average to tell me the story. So like, for instance,

1626
01:26:16,560 --> 01:26:19,679
Speaker 3: Echelon's last poll that we did in Pennsylvania in twenty

1627
01:26:19,720 --> 01:26:22,080
Speaker 3: twenty four had Trump up by a couple of points,

1628
01:26:22,360 --> 01:26:24,320
Speaker 3: and there were not a ton of public polls showing

1629
01:26:24,360 --> 01:26:26,880
Speaker 3: Trump up by a couple of points. I called up

1630
01:26:26,880 --> 01:26:29,640
Speaker 3: one of my other Republican polster friends who was in

1631
01:26:29,680 --> 01:26:31,840
Speaker 3: contact with the campaign. I was like, is this insane?

1632
01:26:32,479 --> 01:26:34,600
Speaker 3: Is our number crazy? Because this is not what the

1633
01:26:34,640 --> 01:26:37,000
Speaker 3: averages are showing. But when you do what we do,

1634
01:26:37,040 --> 01:26:38,559
Speaker 3: like sometimes you just have to put a number out

1635
01:26:38,600 --> 01:26:40,120
Speaker 3: there and you think, either I'm an outlier and I'm

1636
01:26:40,120 --> 01:26:41,200
Speaker 3: going to look like a more and or we're going

1637
01:26:41,240 --> 01:26:42,400
Speaker 3: to look like a genius in the end.

1638
01:26:42,560 --> 01:26:45,120
Speaker 2: But you just have to go with what it says.

1639
01:26:45,479 --> 01:26:49,840
Speaker 3: But I don't mind the averages insofar as I think

1640
01:26:49,920 --> 01:26:54,800
Speaker 3: sometimes outliers happen and they create an enormous amount of

1641
01:26:55,040 --> 01:26:58,040
Speaker 3: panic that if you were looking at it in the

1642
01:26:58,080 --> 01:27:02,160
Speaker 3: context of like what does the other data say, you

1643
01:27:02,200 --> 01:27:05,719
Speaker 3: would know this looks very different. So like the Selleser

1644
01:27:05,800 --> 01:27:08,720
Speaker 3: poll is kind of another example, right, Like that was

1645
01:27:08,920 --> 01:27:10,519
Speaker 3: way outside of what any.

1646
01:27:10,320 --> 01:27:14,840
Speaker 2: Other average show released. It was good that she released it.

1647
01:27:14,880 --> 01:27:17,000
Speaker 3: I will always defend that she released it and was

1648
01:27:17,040 --> 01:27:19,880
Speaker 3: transparent about her methodology, because then someone like me could

1649
01:27:19,880 --> 01:27:23,479
Speaker 3: go in and go, you're not leading on education. Oh okay, no, never, no,

1650
01:27:23,520 --> 01:27:25,400
Speaker 3: thank you, and like, but at least I knew that

1651
01:27:27,000 --> 01:27:30,799
Speaker 3: and that transparency is very important. But having other polls

1652
01:27:30,800 --> 01:27:34,040
Speaker 3: out there that were averaged together meant that I could

1653
01:27:34,120 --> 01:27:38,320
Speaker 3: very quickly see, like, what's the what's the consensus view

1654
01:27:38,760 --> 01:27:41,960
Speaker 3: versus this outlier, and now I can make my judgment accordingly.

1655
01:27:42,840 --> 01:27:44,200
Speaker 2: So I don't mind it. I don't mind it as

1656
01:27:44,240 --> 01:27:44,640
Speaker 2: much as you.

1657
01:27:45,240 --> 01:27:47,840
Speaker 1: Yeah, no, I here's where I really I think on

1658
01:27:47,880 --> 01:27:53,719
Speaker 1: a national level it's okay because there's enough diverse surveys nationally.

1659
01:27:54,200 --> 01:27:57,360
Speaker 1: Where it's a real problem is in the States, because

1660
01:27:58,000 --> 01:28:00,720
Speaker 1: you know, you have certain cheap polsters, right who are

1661
01:28:00,760 --> 01:28:04,720
Speaker 1: just churning out you know, you know, rented day, you know,

1662
01:28:05,040 --> 01:28:07,679
Speaker 1: rented time with you GOV or rented time with others,

1663
01:28:07,720 --> 01:28:13,360
Speaker 1: some sort of uh warehouse of of of a data warehouse,

1664
01:28:13,439 --> 01:28:15,880
Speaker 1: right of of maybe what do you call a panel

1665
01:28:16,280 --> 01:28:20,160
Speaker 1: panelist one of those one of those panels, and you

1666
01:28:20,160 --> 01:28:21,599
Speaker 1: can just turn out a bunch of data and then

1667
01:28:21,600 --> 01:28:24,120
Speaker 1: all of a sudden, one polster has like two thirds

1668
01:28:24,120 --> 01:28:26,760
Speaker 1: of all the polling for that state, right and then

1669
01:28:26,840 --> 01:28:28,479
Speaker 1: and then it sort of can mess it. I just

1670
01:28:28,479 --> 01:28:30,600
Speaker 1: feel like it really is misleading.

1671
01:28:30,120 --> 01:28:31,280
Speaker 2: On the state by state level.

1672
01:28:31,520 --> 01:28:34,840
Speaker 1: It's I I can I can accept the premise that

1673
01:28:34,880 --> 01:28:36,439
Speaker 1: there are times that it can be helpful on the

1674
01:28:36,520 --> 01:28:39,240
Speaker 1: national level, but I've noticed some people try to then

1675
01:28:39,320 --> 01:28:43,000
Speaker 1: combined subgroups and then try to average out subgroups, which

1676
01:28:43,040 --> 01:28:44,560
Speaker 1: seems like a total.

1677
01:28:45,960 --> 01:28:46,000
Speaker 3: No.

1678
01:28:46,880 --> 01:28:48,280
Speaker 2: I should have warded labels applied.

1679
01:28:49,000 --> 01:28:52,760
Speaker 1: Yes, let me close with this, because you you've been

1680
01:28:53,840 --> 01:28:57,240
Speaker 1: I would argue you you sort of made your mark

1681
01:28:57,320 --> 01:29:00,799
Speaker 1: at first being sort of an expert at millennial public opinion.

1682
01:29:03,880 --> 01:29:06,120
Speaker 1: Are we is twenty twenty eight gonna be the first

1683
01:29:06,160 --> 01:29:10,679
Speaker 1: election where millennials outnumber boomers uh in the electorate.

1684
01:29:12,040 --> 01:29:13,120
Speaker 2: Oh, that's a good question.

1685
01:29:14,200 --> 01:29:17,360
Speaker 3: I will it'll be It'll be close.

1686
01:29:18,000 --> 01:29:20,439
Speaker 2: We are a very large generation large.

1687
01:29:20,600 --> 01:29:24,080
Speaker 3: As we have entered middle age, we can begun behaving

1688
01:29:24,120 --> 01:29:27,160
Speaker 3: like middle aged people. We were voting in pretty high numbers.

1689
01:29:28,360 --> 01:29:31,000
Speaker 3: Reddit has accepted that I have entered middle age. It

1690
01:29:31,000 --> 01:29:33,320
Speaker 3: has started feeding me lots of like our slash lawn

1691
01:29:33,360 --> 01:29:36,680
Speaker 3: care content, Like Reddit really thinks I'm a middle aged

1692
01:29:36,760 --> 01:29:40,719
Speaker 3: dad at this point, Lots of lots of motorsports, lawn care.

1693
01:29:40,760 --> 01:29:43,720
Speaker 2: You name it, I digress. Yeah, I mean this is

1694
01:29:43,760 --> 01:29:46,000
Speaker 2: one where crap now. So just so you know, this

1695
01:29:46,080 --> 01:29:49,080
Speaker 2: is what I do for them. Their their life is

1696
01:29:49,080 --> 01:29:49,840
Speaker 2: a them.

1697
01:29:49,840 --> 01:29:53,479
Speaker 3: Don't fail me that card at fifty I.

1698
01:29:53,400 --> 01:29:56,280
Speaker 2: Don't want your card. Mail you anyway.

1699
01:29:57,479 --> 01:30:02,599
Speaker 3: Yeah, the when you look at the data, millennials are

1700
01:30:02,640 --> 01:30:06,040
Speaker 3: still on the one hand, they have moved to the

1701
01:30:06,120 --> 01:30:08,960
Speaker 3: right from where they were during their Obama Yeah.

1702
01:30:09,200 --> 01:30:11,519
Speaker 1: They started so liberal. They only had one direct I

1703
01:30:11,520 --> 01:30:13,920
Speaker 1: would argue there was only one direction, yes, to go right.

1704
01:30:14,000 --> 01:30:18,519
Speaker 3: But they are still more democratic than the gen xers

1705
01:30:18,520 --> 01:30:21,360
Speaker 3: who came before them. And gen Z is still a

1706
01:30:21,400 --> 01:30:27,479
Speaker 3: really big wildcard because gen Z obviously especially gen Z men,

1707
01:30:27,640 --> 01:30:30,360
Speaker 3: began to really gravitate toward Donald Trump. Like they are

1708
01:30:30,400 --> 01:30:34,040
Speaker 3: the ones whose political views are more that like malleable.

1709
01:30:34,320 --> 01:30:36,200
Speaker 3: Where Millennials were a decade or a decade and a

1710
01:30:36,240 --> 01:30:38,439
Speaker 3: half ago, that's where gen Z is right now. They're

1711
01:30:38,520 --> 01:30:40,920
Speaker 3: much more malleable. But I have not seen a great

1712
01:30:40,920 --> 01:30:46,400
Speaker 3: deal of evidence that gen Z is more traditionally ideologically conservative.

1713
01:30:47,120 --> 01:30:50,280
Speaker 1: And so this is gen Z's right now. They're sort

1714
01:30:50,280 --> 01:30:53,439
Speaker 1: of because look, I mean, you know, this data has

1715
01:30:53,439 --> 01:30:55,639
Speaker 1: been very compelling that I've seen, and I'm really into

1716
01:30:55,680 --> 01:30:59,640
Speaker 1: it because I have my household was a gen Z

1717
01:30:59,680 --> 01:31:03,400
Speaker 1: Books script. It was very fun as a political nerd. Right.

1718
01:31:04,200 --> 01:31:06,519
Speaker 1: I have a twenty one year old daughter and an

1719
01:31:06,520 --> 01:31:09,760
Speaker 1: eighteen year old son, and they very much have the

1720
01:31:09,800 --> 01:31:14,120
Speaker 1: influences and what they do. It's they fit the stereotype

1721
01:31:14,120 --> 01:31:17,680
Speaker 1: for better or for worse in many ways, but there

1722
01:31:17,800 --> 01:31:20,439
Speaker 1: is a distinct. In fact, I've been showing my son

1723
01:31:20,560 --> 01:31:22,080
Speaker 1: some of this data and I'm like, does this make

1724
01:31:22,120 --> 01:31:24,760
Speaker 1: sense to you where eighteen to twenty one year olds

1725
01:31:24,760 --> 01:31:28,719
Speaker 1: are politically versus gen Z folks that are essentially older

1726
01:31:28,720 --> 01:31:31,320
Speaker 1: than twenty one? And what it really is, did you

1727
01:31:31,360 --> 01:31:35,800
Speaker 1: experience COVID at home or did you experience COVID in

1728
01:31:35,840 --> 01:31:38,599
Speaker 1: college or above? And it does seem as if that's

1729
01:31:38,640 --> 01:31:42,240
Speaker 1: the line, because both of my kids experience COVID at

1730
01:31:42,240 --> 01:31:46,360
Speaker 1: home right high school, middle school, but there was older

1731
01:31:46,400 --> 01:31:51,160
Speaker 1: gen Z experienced at college and even in young and

1732
01:31:51,160 --> 01:31:53,439
Speaker 1: that seems to be where the dividing line is.

1733
01:31:53,520 --> 01:31:59,040
Speaker 2: Right now, you think that holds? I think so.

1734
01:31:59,520 --> 01:32:01,599
Speaker 3: I think it's to have ripple effects for a long

1735
01:32:01,640 --> 01:32:04,120
Speaker 3: time to come. Depends on how the we're defining holds.

1736
01:32:04,120 --> 01:32:07,160
Speaker 3: But there is a great writer about gen Z. Her

1737
01:32:07,240 --> 01:32:09,920
Speaker 3: name's Rachel Jenfaza. She has a think a substack called

1738
01:32:09,960 --> 01:32:12,000
Speaker 3: the up and up, and it is you know, she

1739
01:32:12,160 --> 01:32:16,000
Speaker 3: has really been the person that has posited this as

1740
01:32:16,640 --> 01:32:18,840
Speaker 3: when we think about gen Z as a as a

1741
01:32:18,880 --> 01:32:21,720
Speaker 3: whole group, we're missing that there is this dividing line

1742
01:32:21,720 --> 01:32:23,680
Speaker 3: and it is exactly what you're talking about. It is

1743
01:32:23,720 --> 01:32:27,800
Speaker 3: what was your experience of COVID was it you were

1744
01:32:27,840 --> 01:32:30,040
Speaker 3: already out on your own, maybe you were in college,

1745
01:32:30,080 --> 01:32:33,360
Speaker 3: you were navigating it as an independent adult, versus I

1746
01:32:33,400 --> 01:32:34,360
Speaker 3: didn't have a problem.

1747
01:32:34,840 --> 01:32:36,320
Speaker 2: I didn't have a high school graduation.

1748
01:32:36,640 --> 01:32:39,439
Speaker 3: I was unable to go hang out with friends in

1749
01:32:39,479 --> 01:32:43,479
Speaker 3: person for some of the most arguably important years of

1750
01:32:43,479 --> 01:32:46,840
Speaker 3: my life to do that. So you're I think you're

1751
01:32:46,880 --> 01:32:49,440
Speaker 3: completely right. But I don't know what the political implications

1752
01:32:49,439 --> 01:32:51,800
Speaker 3: of that for a long time to come, except I

1753
01:32:51,800 --> 01:32:55,360
Speaker 3: imagine it will leave some lingering skepticism about like trusted

1754
01:32:55,479 --> 01:32:59,000
Speaker 3: institutions and trust in others. Like That's one of the

1755
01:32:59,000 --> 01:33:02,360
Speaker 3: things that I think makes me the most worried about

1756
01:33:02,360 --> 01:33:04,280
Speaker 3: our country for the future and sort of sad for

1757
01:33:04,360 --> 01:33:07,600
Speaker 3: younger generations is in order for society to function, you

1758
01:33:07,640 --> 01:33:10,759
Speaker 3: need high social trust. You need high numbers of people

1759
01:33:11,040 --> 01:33:13,280
Speaker 3: believing that if they drop their wallet on the street,

1760
01:33:13,360 --> 01:33:15,400
Speaker 3: someone's going to return it to them. You need high

1761
01:33:15,439 --> 01:33:19,760
Speaker 3: numbers of people believing that you can generally count on

1762
01:33:19,800 --> 01:33:21,680
Speaker 3: other people to do the right thing. It's okay to

1763
01:33:21,720 --> 01:33:24,280
Speaker 3: be skeptical, it's okay to be on guard. But if

1764
01:33:24,320 --> 01:33:27,680
Speaker 3: society overwhelmingly believes people cannot be trusted to do the

1765
01:33:27,720 --> 01:33:30,960
Speaker 3: right thing, like, everything start to really break down. And

1766
01:33:31,000 --> 01:33:33,120
Speaker 3: that is where a lot of gen z is that

1767
01:33:33,439 --> 01:33:35,800
Speaker 3: they're just the kind of thing you cannot trust other

1768
01:33:35,840 --> 01:33:37,519
Speaker 3: people to do the right thing. The world is a

1769
01:33:37,600 --> 01:33:40,439
Speaker 3: dark and scary place, and that has a lot of

1770
01:33:40,439 --> 01:33:42,599
Speaker 3: second and third order effects that may be very nervous.

1771
01:33:43,120 --> 01:33:46,599
Speaker 1: You know, boomers were more evenly divided than we thought, Right,

1772
01:33:46,680 --> 01:33:49,760
Speaker 1: it's a very fifty to fifty generation over if you

1773
01:33:49,800 --> 01:33:53,840
Speaker 1: look at it through a longer lens, do you concur

1774
01:33:53,880 --> 01:33:54,120
Speaker 1: with that?

1775
01:33:55,160 --> 01:33:55,360
Speaker 2: Yeah?

1776
01:33:55,880 --> 01:33:58,360
Speaker 3: I feel like I recall a lot of polls, both

1777
01:33:58,400 --> 01:34:00,400
Speaker 3: in the twenty twenty election as well as this one

1778
01:34:00,400 --> 01:34:03,360
Speaker 3: where you know, this is the the Obama era to

1779
01:34:03,640 --> 01:34:06,240
Speaker 3: your earlier point from where for when we started talking that, like,

1780
01:34:06,439 --> 01:34:11,680
Speaker 3: was the Obama era the abnormality? You had huge generational

1781
01:34:11,720 --> 01:34:16,960
Speaker 3: differences there where you had boomers massively by Obama in

1782
01:34:17,000 --> 01:34:19,679
Speaker 3: some ways, and you had young people massively pro Obama.

1783
01:34:19,760 --> 01:34:21,920
Speaker 3: And then when tru it becomes Trump and Biden, like,

1784
01:34:21,960 --> 01:34:26,160
Speaker 3: some of that kind of levels out and boomers who

1785
01:34:26,160 --> 01:34:29,720
Speaker 3: had did not like Obama suddenly liked Biden or you know,

1786
01:34:30,320 --> 01:34:37,240
Speaker 3: their their previous more progressive viewpoints like began to come

1787
01:34:37,280 --> 01:34:40,040
Speaker 3: back out, where for younger people they went the other way.

1788
01:34:40,320 --> 01:34:42,559
Speaker 1: How important? Last question we get chat on this because

1789
01:34:42,680 --> 01:34:46,800
Speaker 1: I just I'm obsessed with generations? How important do you think?

1790
01:34:47,040 --> 01:34:48,559
Speaker 1: Let me let me let me well, let me just

1791
01:34:48,560 --> 01:34:51,679
Speaker 1: put it in this form. So I look at I'm

1792
01:34:51,720 --> 01:34:54,240
Speaker 1: gen X. I'm right in the middle of gen X. Okay,

1793
01:34:54,320 --> 01:34:56,760
Speaker 1: i am smack dab in the middle. There's no like,

1794
01:34:56,960 --> 01:34:59,920
Speaker 1: you know, gray area. For me, born in the early set,

1795
01:35:01,960 --> 01:35:03,960
Speaker 1: and my coming of age was Reagan. That's what I

1796
01:35:04,000 --> 01:35:06,240
Speaker 1: always say, right, meaning you know we were you know,

1797
01:35:06,280 --> 01:35:09,240
Speaker 1: Reagan was the first celebrated president of our awareness. I

1798
01:35:09,280 --> 01:35:12,240
Speaker 1: certainly was aware of Carter, but Reagan was it. For millennials,

1799
01:35:12,320 --> 01:35:16,000
Speaker 1: arguably it's Bill Clinton, right like that is the and

1800
01:35:17,280 --> 01:35:20,040
Speaker 1: for boomers it's sort of broken in two. Right, you

1801
01:35:20,120 --> 01:35:24,439
Speaker 1: have older boomers it was Eisenhower younger boomers. It's Kennedy Johnson.

1802
01:35:25,360 --> 01:35:29,240
Speaker 1: I'm curious how much is that first impression it feels.

1803
01:35:29,640 --> 01:35:35,920
Speaker 1: How how sticky is politics in your twenties versus your sixties,

1804
01:35:36,400 --> 01:35:39,200
Speaker 1: Meaning if you're sort of leaning left in your twenties,

1805
01:35:39,520 --> 01:35:42,479
Speaker 1: are you always going to be? Is there enough data

1806
01:35:42,560 --> 01:35:46,280
Speaker 1: now to prove that you're probably going to stay that way? Yeah,

1807
01:35:46,320 --> 01:35:48,479
Speaker 1: you may vacillate a little bit, right, you may move

1808
01:35:48,520 --> 01:35:50,400
Speaker 1: a little bit, but for the most part, you're going

1809
01:35:50,479 --> 01:35:54,200
Speaker 1: to stay sort of in that one quadrant. And I

1810
01:35:54,240 --> 01:35:56,720
Speaker 1: wonder just how much that is just of who was

1811
01:35:56,760 --> 01:36:00,479
Speaker 1: your presence, who was Was there a successful press or

1812
01:36:00,520 --> 01:36:03,600
Speaker 1: an unsuccessful president in your coming of age period? And

1813
01:36:04,120 --> 01:36:07,320
Speaker 1: was that the influential moment. Is there enough scholarship there

1814
01:36:07,320 --> 01:36:09,240
Speaker 1: to sort of draw some conclusions.

1815
01:36:09,720 --> 01:36:14,320
Speaker 3: Yeah, there's a number of different studies that suggest things

1816
01:36:14,320 --> 01:36:17,160
Speaker 3: that happened to you when you are younger have I

1817
01:36:17,160 --> 01:36:19,519
Speaker 3: think there's one study I used to cite all the time.

1818
01:36:19,680 --> 01:36:21,679
Speaker 3: It was like three to four times as much effect

1819
01:36:21,680 --> 01:36:24,600
Speaker 3: on your lifetime political behavior or something that happens in

1820
01:36:24,640 --> 01:36:27,240
Speaker 3: your twenties versus something that happens in your forties, Like

1821
01:36:27,280 --> 01:36:29,680
Speaker 3: by the time you've reached your forties, your worldview is

1822
01:36:29,800 --> 01:36:31,000
Speaker 3: pretty set.

1823
01:36:30,840 --> 01:36:31,599
Speaker 2: At that point.

1824
01:36:32,240 --> 01:36:34,679
Speaker 3: You can still change your mind, but it's much more

1825
01:36:34,800 --> 01:36:37,720
Speaker 3: established than when you're twenty. But I think it's the

1826
01:36:38,080 --> 01:36:42,880
Speaker 3: finding was it less around presidents and more around events.

1827
01:36:42,960 --> 01:36:46,240
Speaker 3: So like I would argue that for millennials, the formative

1828
01:36:46,320 --> 01:36:49,160
Speaker 3: things are less Bill Clinton and George W. Bush and

1829
01:36:49,280 --> 01:36:52,960
Speaker 3: more nine to eleven financial crisis, got a rap war.

1830
01:36:54,280 --> 01:36:58,439
Speaker 3: For gen Z, it's gonna be less like Joe Biden

1831
01:36:59,080 --> 01:37:06,360
Speaker 3: and more Black Lives Matter, Uh, COVID Trump, I mean

1832
01:37:06,400 --> 01:37:09,600
Speaker 3: Trump and Trump I think exists as an event in

1833
01:37:09,640 --> 01:37:10,919
Speaker 3: addition to being a president.

1834
01:37:11,280 --> 01:37:14,320
Speaker 1: No, No, he's bigger than Look, he's the most influential president

1835
01:37:14,360 --> 01:37:15,519
Speaker 1: culturally since FDR.

1836
01:37:16,760 --> 01:37:20,080
Speaker 2: Yeah, I really you know so I think.

1837
01:37:19,880 --> 01:37:22,120
Speaker 3: You are right, And I think this affects the way

1838
01:37:22,160 --> 01:37:25,960
Speaker 3: that gen Z thinks about how politics ought to be conducted,

1839
01:37:26,400 --> 01:37:32,080
Speaker 3: which is why I think this like populist aggressive, uh,

1840
01:37:32,360 --> 01:37:37,040
Speaker 3: not playing by the like traditional rules of communication approach.

1841
01:37:37,880 --> 01:37:40,000
Speaker 3: That's that is just all gen Z has ever known.

1842
01:37:40,080 --> 01:37:42,000
Speaker 3: So to them, like, of course that makes sense of

1843
01:37:42,080 --> 01:37:45,080
Speaker 3: how that's how you should communicate. That's how everything is communicated.

1844
01:37:45,280 --> 01:37:46,320
Speaker 3: Politics is combat.

1845
01:37:48,800 --> 01:37:51,559
Speaker 1: Kristen Sulta Sanderson I always learn every time I talk

1846
01:37:51,600 --> 01:37:55,000
Speaker 1: to you, I learned something, and this I could keep going.

1847
01:37:55,040 --> 01:37:56,320
Speaker 1: We went literally an hour.

1848
01:37:56,479 --> 01:37:58,440
Speaker 2: Well I have been learning from you for a decade.

1849
01:37:58,120 --> 01:38:01,400
Speaker 1: And a half, so well it is. And I hope folks.

1850
01:38:01,640 --> 01:38:03,719
Speaker 1: Do you do a substack or is it just Raffini,

1851
01:38:03,760 --> 01:38:04,880
Speaker 1: your business partner that does so.

1852
01:38:04,960 --> 01:38:07,559
Speaker 3: I have a substack and I mostly use it when

1853
01:38:07,760 --> 01:38:10,280
Speaker 3: so I'm a contributing opinion writer at the New York Times.

1854
01:38:10,400 --> 01:38:12,080
Speaker 3: When I have an idea that it is too weird

1855
01:38:12,120 --> 01:38:14,640
Speaker 3: or off the wall for them, it goes to my substack.

1856
01:38:15,080 --> 01:38:17,200
Speaker 1: That's how I've decided to use substack. I no longer

1857
01:38:17,240 --> 01:38:19,120
Speaker 1: I'm like, no, I'm just going to do it. You know,

1858
01:38:19,400 --> 01:38:21,639
Speaker 1: I don't want some editor deciding whether this is worthy

1859
01:38:21,680 --> 01:38:22,240
Speaker 1: of publishing.

1860
01:38:22,640 --> 01:38:24,400
Speaker 2: I will decide that's fun.

1861
01:38:25,080 --> 01:38:28,800
Speaker 1: Well, anyway, if you weren't from I hope if folks

1862
01:38:28,840 --> 01:38:30,760
Speaker 1: weren't familiar with you, they are now and they will

1863
01:38:31,160 --> 01:38:33,240
Speaker 1: only want to get more insight from me all the time.

1864
01:38:33,520 --> 01:38:35,760
Speaker 2: Kristen, this was a pleasure. Thanks, thank you.

1865
01:38:35,880 --> 01:38:47,920
Speaker 1: Check Well, I hope you enjoyed that conversation with Kristin.

1866
01:38:48,080 --> 01:38:50,160
Speaker 1: I will tell you this, I hope send me your

1867
01:38:50,200 --> 01:38:52,120
Speaker 1: thoughts on that in fact, there's a whole bunch of

1868
01:38:52,160 --> 01:38:56,840
Speaker 1: I I was going to lead this episode with my

1869
01:38:57,720 --> 01:39:01,639
Speaker 1: everything I learned from that queue validated voter survey that

1870
01:39:02,400 --> 01:39:05,080
Speaker 1: Kristin and I were knee deeping and keeeking out on.

1871
01:39:05,840 --> 01:39:07,960
Speaker 1: I still think I have more to say about that

1872
01:39:08,080 --> 01:39:10,000
Speaker 1: and a few things. So the big for me, the

1873
01:39:10,000 --> 01:39:12,560
Speaker 1: big takeaway was, first of all, I do think the

1874
01:39:13,920 --> 01:39:16,639
Speaker 1: the Obama bubble, if you will, right, and I think

1875
01:39:16,680 --> 01:39:19,839
Speaker 1: there was an Obama demographic bubble that he did create

1876
01:39:20,320 --> 01:39:25,840
Speaker 1: that has totally dissipated. The Republicans are doing as well

1877
01:39:25,960 --> 01:39:29,559
Speaker 1: with African American voters now as they were four years before.

1878
01:39:29,560 --> 01:39:33,240
Speaker 1: Obama was the first was the nominee for the Democratic Party,

1879
01:39:33,680 --> 01:39:36,840
Speaker 1: So in some ways that is and I have always

1880
01:39:36,880 --> 01:39:39,080
Speaker 1: been a bit skeptical that this is a oh the

1881
01:39:39,360 --> 01:39:42,639
Speaker 1: Democrats have a black voter problem. You know, they're doing

1882
01:39:42,680 --> 01:39:45,960
Speaker 1: just as well with African American voters, if not better

1883
01:39:46,000 --> 01:39:48,679
Speaker 1: than they did with Kerrie, better than they did with Gore. Okay,

1884
01:39:48,680 --> 01:39:50,600
Speaker 1: it's not as good as it was with Obama and

1885
01:39:50,680 --> 01:39:53,559
Speaker 1: the first election after Obama, or certainly with Obama's vice president.

1886
01:39:53,600 --> 01:39:57,839
Speaker 1: But I think you've seen there's always been somewhere between

1887
01:39:57,880 --> 01:40:01,120
Speaker 1: ten and twenty percent of African Americans who vote more

1888
01:40:01,120 --> 01:40:04,640
Speaker 1: in ideology than than necessarily on the on some of

1889
01:40:04,680 --> 01:40:07,880
Speaker 1: these civil rights issues and more on. And I think

1890
01:40:07,880 --> 01:40:11,760
Speaker 1: that that's you know, a chunk of conservatives in that

1891
01:40:11,840 --> 01:40:15,519
Speaker 1: demographic if not anything else. And then there's always been

1892
01:40:16,000 --> 01:40:19,360
Speaker 1: some cultural issues that Republicans have always been able to

1893
01:40:19,360 --> 01:40:23,280
Speaker 1: have some success at wolling certain certain groups that maybe

1894
01:40:23,360 --> 01:40:24,720
Speaker 1: vote largely.

1895
01:40:24,240 --> 01:40:26,439
Speaker 2: On one side, but but do split off.

1896
01:40:27,040 --> 01:40:31,479
Speaker 1: And then with Hispanic Americans, you know, people forget.

1897
01:40:31,479 --> 01:40:34,000
Speaker 2: In two thousand and four, George W. Bush carried forty four.

1898
01:40:33,880 --> 01:40:37,479
Speaker 1: Percent of Hispanic Americans and Donald Trump is up to

1899
01:40:37,560 --> 01:40:39,479
Speaker 1: forty eight percent. So I do think that there is

1900
01:40:40,000 --> 01:40:43,120
Speaker 1: there is that this is in some ways, and in fact,

1901
01:40:43,160 --> 01:40:45,280
Speaker 1: I think the Democratic Party spent too much time worrying

1902
01:40:45,280 --> 01:40:48,240
Speaker 1: about each demographic group separately when the fact is having

1903
01:40:48,280 --> 01:40:52,439
Speaker 1: a holistic message, see because it does. It did seem

1904
01:40:52,479 --> 01:40:55,920
Speaker 1: as if Donald Trump's message appealed to everybody and then

1905
01:40:55,960 --> 01:40:58,600
Speaker 1: he picked it he improved with every demographic group. But

1906
01:40:58,680 --> 01:41:01,200
Speaker 1: that's what you're seeing. You don't have a demographic problem.

1907
01:41:01,240 --> 01:41:03,479
Speaker 1: You have a message problem, right, you have an issue problem.

1908
01:41:03,520 --> 01:41:05,920
Speaker 1: You don't have a specific demographic group problem. And I

1909
01:41:05,960 --> 01:41:09,320
Speaker 1: do think that the Democratic Party is always worried about

1910
01:41:09,479 --> 01:41:11,479
Speaker 1: as my friend Chris Matthews just to call it playing

1911
01:41:11,479 --> 01:41:13,760
Speaker 1: the correct note on a xylophone. They were always looking

1912
01:41:13,760 --> 01:41:17,240
Speaker 1: for the correct note when to play, versus having the

1913
01:41:17,320 --> 01:41:22,400
Speaker 1: right melody. And I think that that's that's that's the

1914
01:41:22,640 --> 01:41:23,320
Speaker 1: that's the issue there.

1915
01:41:23,320 --> 01:41:26,040
Speaker 2: All right, let's get to a couple of questions here.

1916
01:41:27,360 --> 01:41:30,880
Speaker 1: Big birthday week. I love the fourth of July. I'm

1917
01:41:30,920 --> 01:41:34,759
Speaker 1: a big Independence Day fan. It's it's because I always

1918
01:41:34,800 --> 01:41:37,080
Speaker 1: I always see it as an opportunity for us to

1919
01:41:37,120 --> 01:41:40,240
Speaker 1: talk about the founding, talk about the Constitution, talk about

1920
01:41:40,240 --> 01:41:43,160
Speaker 1: the phrase more perfect union. So that's why, you know,

1921
01:41:43,240 --> 01:41:45,120
Speaker 1: as a as a bit of a history geek, I

1922
01:41:45,200 --> 01:41:45,840
Speaker 1: get into it.

1923
01:41:46,120 --> 01:41:48,840
Speaker 2: But anyway, let's get to some ass chot ass chuck.

1924
01:41:52,720 --> 01:41:53,040
Speaker 3: All right.

1925
01:41:53,080 --> 01:41:56,560
Speaker 1: First question comes from Kevin from Bloomington, Minnesota.

1926
01:41:56,920 --> 01:41:59,360
Speaker 2: Here's a fun fact. My mom was born in Bloomington, Illinois.

1927
01:41:59,479 --> 01:42:03,639
Speaker 1: I love all Theloomington's. Bloomington, Indiana home of the home

1928
01:42:03,640 --> 01:42:05,839
Speaker 1: of the Bloomington Minnisote, I think is just a suburb.

1929
01:42:05,920 --> 01:42:08,800
Speaker 1: I believe boy, I'm going to get that wrong. Bloomington, Indiana,

1930
01:42:08,840 --> 01:42:12,559
Speaker 1: of course, is the home of the Indiana University Bloomington, Illinois,

1931
01:42:13,120 --> 01:42:17,679
Speaker 1: home of State Farm. Anyway, but I digress the episode.

1932
01:42:17,720 --> 01:42:20,160
Speaker 1: Here's the question from Kevin. The episode with Mark Leevivich

1933
01:42:20,280 --> 01:42:22,599
Speaker 1: was the best one yet. I really enjoyed the engaging

1934
01:42:22,600 --> 01:42:25,920
Speaker 1: conversation about politics, sports books, and Beatles. What ifs you

1935
01:42:26,000 --> 01:42:29,200
Speaker 1: two talked about the Marlins and you mentioned naming the

1936
01:42:29,200 --> 01:42:31,439
Speaker 1: team the Florida Marlins over the Miami Marlins was a

1937
01:42:31,479 --> 01:42:32,040
Speaker 1: huge mistake.

1938
01:42:32,080 --> 01:42:32,240
Speaker 3: Why?

1939
01:42:32,320 --> 01:42:34,760
Speaker 1: Looking at my hometown teens, I don't think the Minneapolis

1940
01:42:34,800 --> 01:42:38,360
Speaker 1: Twins are the Saint Paul Wilde name shifts would affect much.

1941
01:42:38,400 --> 01:42:40,120
Speaker 1: But then again, I live in the Twin Cities, so

1942
01:42:40,200 --> 01:42:43,280
Speaker 1: maybe that's part of it. Bonus question should have should

1943
01:42:43,280 --> 01:42:46,200
Speaker 1: the NHL Florida Panthers gone with a city name? Keep

1944
01:42:46,200 --> 01:42:49,240
Speaker 1: the great podcast and Inside coming. Okay, I'm obsessed with

1945
01:42:49,240 --> 01:42:50,680
Speaker 1: this and I'll tell you why. So I went to

1946
01:42:50,720 --> 01:42:57,280
Speaker 1: Cuba in two thousand. It was an eye opening experience.

1947
01:42:57,720 --> 01:43:02,760
Speaker 1: If you have doubts about if you want to understand

1948
01:43:02,760 --> 01:43:06,639
Speaker 1: why communism and socialism doesn't work in its fullest form,

1949
01:43:06,840 --> 01:43:10,200
Speaker 1: go to Cuba and you'll see it right just it was.

1950
01:43:10,320 --> 01:43:12,760
Speaker 1: It was an important trip. I'm glad I went. Fascinating

1951
01:43:12,800 --> 01:43:19,559
Speaker 1: incredible people, what a beautiful country it could be. And

1952
01:43:19,640 --> 01:43:21,920
Speaker 1: yes I did I love Ernest Hemingway. I loved doing

1953
01:43:21,920 --> 01:43:23,840
Speaker 1: all that Hemingway stuff that I was there. Anyway, I'm

1954
01:43:23,840 --> 01:43:26,640
Speaker 1: not going to get into everything I did there, but

1955
01:43:26,680 --> 01:43:29,360
Speaker 1: I do think my I don't at this point, I

1956
01:43:29,360 --> 01:43:31,960
Speaker 1: don't think I'm committing as I joke, I don't think

1957
01:43:31,960 --> 01:43:33,640
Speaker 1: I was committing a crime. But obviously I went through

1958
01:43:33,680 --> 01:43:36,759
Speaker 1: another country in order to go to Cuba at that time,

1959
01:43:36,920 --> 01:43:40,760
Speaker 1: although now you can do it, I think through you know, precariously,

1960
01:43:40,800 --> 01:43:44,280
Speaker 1: but through various means. But it was amazing the importance

1961
01:43:44,320 --> 01:43:48,680
Speaker 1: of Miami, not Florida, but Miami to that population. And

1962
01:43:48,720 --> 01:43:52,720
Speaker 1: it's not just Cuba, okay. Miami is the capital, unofficial

1963
01:43:52,720 --> 01:43:56,599
Speaker 1: capital of Latin America. All right, No offense to save

1964
01:43:56,680 --> 01:44:00,280
Speaker 1: Paul or Minneapolis. But there's no like north Star to

1965
01:44:00,280 --> 01:44:03,120
Speaker 1: borrow a phrase, although I missed the Minnesota north Stars,

1966
01:44:04,520 --> 01:44:09,400
Speaker 1: where it is representative of a community sort of bigger

1967
01:44:09,920 --> 01:44:13,760
Speaker 1: than the state itself. Miami is is bigger than the

1968
01:44:13,800 --> 01:44:18,439
Speaker 1: state of Florida as a cultural icon, particularly the Latin America.

1969
01:44:18,880 --> 01:44:22,840
Speaker 1: Everybody in Colombia knows Miami, okay, And yes they know

1970
01:44:22,840 --> 01:44:25,800
Speaker 1: Miami's in Florida. But Miami is the is the is

1971
01:44:25,840 --> 01:44:29,559
Speaker 1: the star. Okay, everybody in Rio knows Miami. Everybody in

1972
01:44:29,640 --> 01:44:34,360
Speaker 1: Buenos Aires knows Miami. It is in here. Baseball is

1973
01:44:34,720 --> 01:44:40,280
Speaker 1: the sport of Latin America along with America, with with soccer.

1974
01:44:41,000 --> 01:44:46,120
Speaker 1: And you have these two incredible. You have Miami, which

1975
01:44:46,160 --> 01:44:48,559
Speaker 1: is so to sit there and call it and you know,

1976
01:44:48,760 --> 01:44:52,000
Speaker 1: look what really chops my you know what on that is.

1977
01:44:52,080 --> 01:44:54,479
Speaker 1: Wayne Heysange, who is the founding owner of the Marlins,

1978
01:44:55,000 --> 01:44:58,200
Speaker 1: had to burrow up his ass about Miami. He was

1979
01:44:58,200 --> 01:45:01,040
Speaker 1: a Fort Lauderdale guy, but he also had this misnomer

1980
01:45:01,080 --> 01:45:05,720
Speaker 1: that somehow that Miami would be the state of Florida's team. Well,

1981
01:45:05,720 --> 01:45:08,240
Speaker 1: if you know anything about this state of Florida, Miami

1982
01:45:08,280 --> 01:45:10,920
Speaker 1: has been the outcast of the rest of Florida. If

1983
01:45:10,920 --> 01:45:12,680
Speaker 1: you wanted to win in Florida politics, you used to

1984
01:45:12,760 --> 01:45:16,200
Speaker 1: run against Miami. You know. Bob Graham thickened up his

1985
01:45:16,320 --> 01:45:18,439
Speaker 1: Southern accent because he didn't want people to realize he

1986
01:45:18,520 --> 01:45:21,439
Speaker 1: was from Miami. You know, a Republicans were able to

1987
01:45:21,479 --> 01:45:26,000
Speaker 1: win from Miami as friendly to Cubans, but Democrats in particular,

1988
01:45:26,640 --> 01:45:30,439
Speaker 1: but in general, the central and North part always very

1989
01:45:30,479 --> 01:45:33,360
Speaker 1: skeptical of Miami. Same way, why it was so hard

1990
01:45:33,400 --> 01:45:36,280
Speaker 1: for mayor of Philadelphia before I had Rendell to win

1991
01:45:36,400 --> 01:45:38,599
Speaker 1: statewide there. A mayor of New York City has had

1992
01:45:38,600 --> 01:45:41,200
Speaker 1: to find out how many times they've won statewide in

1993
01:45:41,200 --> 01:45:44,640
Speaker 1: New York. So there's always been so you know, I

1994
01:45:44,680 --> 01:45:47,280
Speaker 1: think I didn't understand the culture of the state of

1995
01:45:47,320 --> 01:45:49,880
Speaker 1: Florida versus the state of Miami. Number one, But it's

1996
01:45:49,880 --> 01:45:51,960
Speaker 1: all about what I just said there. Miami is the

1997
01:45:51,960 --> 01:45:55,040
Speaker 1: capital of Latin America. Why wouldn't you have that? They

1998
01:45:55,080 --> 01:45:58,799
Speaker 1: could have been Latin America's baseball team before the Miami

1999
01:45:58,800 --> 01:46:02,200
Speaker 1: Marlins existed. There was no doubt Latin America's baseball team

2000
01:46:02,400 --> 01:46:08,200
Speaker 1: was mostly the New York Yankees, somewhat the Dodgers. Miami

2001
01:46:08,240 --> 01:46:13,120
Speaker 1: could have been that, and the poor beginning of that franchise,

2002
01:46:13,479 --> 01:46:18,400
Speaker 1: the absolute idiotic ownership structure and decision making and all

2003
01:46:18,439 --> 01:46:22,160
Speaker 1: of those things. Major League Baseball has messed up the

2004
01:46:22,200 --> 01:46:28,559
Speaker 1: two Florida franchises so badly. Bad ownership groups multiple times

2005
01:46:28,560 --> 01:46:32,559
Speaker 1: in each side, bad decision making on stadium deals, bad

2006
01:46:32,600 --> 01:46:36,200
Speaker 1: decision banking on teams. It's almost as if Baseball didn't

2007
01:46:36,240 --> 01:46:38,800
Speaker 1: want Florida to the state of Florida. To succeed having

2008
01:46:38,840 --> 01:46:41,679
Speaker 1: baseball teams, they went out of their way to make

2009
01:46:41,760 --> 01:46:47,520
Speaker 1: sure they were either incompetent ownership groups terrible actual locations

2010
01:46:47,520 --> 01:46:51,000
Speaker 1: for their stadiums. Both Saint Pete the worst place you

2011
01:46:51,040 --> 01:46:53,120
Speaker 1: could put a baseball stadium in order to attract an

2012
01:46:53,280 --> 01:46:55,840
Speaker 1: entire region, all right, should have been in the city

2013
01:46:55,880 --> 01:46:59,360
Speaker 1: of Tampa and literally at a football stadium in the

2014
01:46:59,840 --> 01:47:02,679
Speaker 1: northwest corner of my Dade County was the worst place

2015
01:47:02,720 --> 01:47:05,439
Speaker 1: you could put a baseball franchise for as lung as

2016
01:47:05,439 --> 01:47:09,160
Speaker 1: they did. So I get my backup that Miami's not

2017
01:47:09,200 --> 01:47:11,519
Speaker 1: considered a good sports towern It's like, no, we've had

2018
01:47:11,560 --> 01:47:16,040
Speaker 1: bad owners with bad stadiums, and that's why.

2019
01:47:16,120 --> 01:47:18,800
Speaker 2: The fans haven't had a chance. All right, Hey, Kevin,

2020
01:47:18,840 --> 01:47:20,640
Speaker 2: thanks for letting me get that off my back. All right.

2021
01:47:20,680 --> 01:47:24,759
Speaker 1: Second question, this comes from Dakota. Doesn't say where.

2022
01:47:25,080 --> 01:47:27,040
Speaker 2: Maybe he's from one of the Dakotas, but I will

2023
01:47:27,040 --> 01:47:27,639
Speaker 2: not speculate.

2024
01:47:28,120 --> 01:47:30,639
Speaker 1: Hey, Jock, really enjoy your new format. You're inside analysis

2025
01:47:30,680 --> 01:47:32,720
Speaker 1: are always on parallel. Do you think the media is

2026
01:47:32,760 --> 01:47:34,880
Speaker 1: failing the American people and how it covers Donald Trump,

2027
01:47:34,960 --> 01:47:37,479
Speaker 1: especially with his flood the zone strategy. For example, I

2028
01:47:37,479 --> 01:47:39,760
Speaker 1: find it outrageous that Trump didn't attend the funeral of

2029
01:47:39,800 --> 01:47:43,320
Speaker 1: Melissa and Mark Cortman. I agree with that if the

2030
01:47:43,400 --> 01:47:45,679
Speaker 1: rules were reversed, the coverage would be NonStop. Why isn't

2031
01:47:45,680 --> 01:47:48,439
Speaker 1: this a bigger story? Well, it's interesting, but you know,

2032
01:47:48,479 --> 01:47:50,400
Speaker 1: at this point, what do you measure? If more people

2033
01:47:50,400 --> 01:47:53,280
Speaker 1: are getting their news from streaming, then from cable and

2034
01:47:53,320 --> 01:47:57,120
Speaker 1: broadcast combine, if more people are getting their news from YouTube,

2035
01:47:57,120 --> 01:48:00,320
Speaker 1: then there because plenty of people are covering this, think

2036
01:48:00,320 --> 01:48:03,320
Speaker 1: what you know, you're lamenting, you know, and I think

2037
01:48:03,320 --> 01:48:05,840
Speaker 1: when people point out why isn't the media doing this?

2038
01:48:06,520 --> 01:48:09,080
Speaker 1: There were referencing a media if that doesn't exist anymore.

2039
01:48:09,160 --> 01:48:12,760
Speaker 1: When the media was the New York Times, the major networks,

2040
01:48:12,920 --> 01:48:15,120
Speaker 1: maybe the Washington Post, maybe the Wall Street Journal. Right,

2041
01:48:15,240 --> 01:48:18,439
Speaker 1: they could sort of set the agenda, if you will, right,

2042
01:48:18,520 --> 01:48:22,240
Speaker 1: and it would and you know, they would not move together,

2043
01:48:22,360 --> 01:48:27,240
Speaker 1: but certainly they they sort of you know, certainly didn't

2044
01:48:27,280 --> 01:48:31,160
Speaker 1: move against each other, if you will. And I do

2045
01:48:31,200 --> 01:48:34,880
Speaker 1: think that we seem to move on quicker in different ways.

2046
01:48:34,960 --> 01:48:38,680
Speaker 1: Part of it again, Donald Trump has certainly broken you know,

2047
01:48:38,760 --> 01:48:42,400
Speaker 1: he's sort of he has sort of made the so

2048
01:48:42,479 --> 01:48:46,040
Speaker 1: called mainstream media or traditional media cower if you will, right,

2049
01:48:46,120 --> 01:48:48,759
Speaker 1: You've got a whole bunch of people afraid of asking

2050
01:48:48,800 --> 01:48:51,080
Speaker 1: him tough questions because their bosses don't want to ask

2051
01:48:51,120 --> 01:48:53,240
Speaker 1: him tough questions in the oval, or they still want

2052
01:48:53,280 --> 01:48:55,599
Speaker 1: to have access. So I think there's some of that,

2053
01:48:57,280 --> 01:49:00,240
Speaker 1: But I, you know, I kind of think that the

2054
01:49:00,360 --> 01:49:07,360
Speaker 1: collective independent media, the influencer media throwing the truth. I think,

2055
01:49:07,439 --> 01:49:10,160
Speaker 1: you know, you put it all together. You look at

2056
01:49:10,200 --> 01:49:14,040
Speaker 1: his poll ratings, and you let me ask you if

2057
01:49:14,880 --> 01:49:18,799
Speaker 1: if the media we're doing such a terrible job reporting

2058
01:49:18,800 --> 01:49:22,240
Speaker 1: on Donald Trump, why is he so unpopular? So, I,

2059
01:49:22,400 --> 01:49:24,519
Speaker 1: you know, I take your point. I think what you

2060
01:49:24,920 --> 01:49:26,599
Speaker 1: what you're pointing out is that we don't have these

2061
01:49:26,760 --> 01:49:28,760
Speaker 1: feeding frenzy moments anymore. But I don't think we're ever

2062
01:49:28,800 --> 01:49:30,920
Speaker 1: going to have these, you know, unless it's just like

2063
01:49:31,120 --> 01:49:33,800
Speaker 1: one super gigantic event. I mean, just look at the

2064
01:49:33,840 --> 01:49:36,960
Speaker 1: coverage of Iran that becomes the biggest story in the

2065
01:49:37,000 --> 01:49:39,080
Speaker 1: world for forty eight hours and then everybody's walking away

2066
01:49:39,080 --> 01:49:42,320
Speaker 1: from it. I know, by the way, I you know,

2067
01:49:42,560 --> 01:49:44,880
Speaker 1: did it go so well? You know, now we've got

2068
01:49:44,920 --> 01:49:50,360
Speaker 1: a second intelligence leak indicating that Iran was surprised at

2069
01:49:50,400 --> 01:49:55,760
Speaker 1: how much of their nuclear capabilities remain, you know, while

2070
01:49:55,800 --> 01:49:58,599
Speaker 1: the tactical While it may have looked like a tactical

2071
01:49:58,640 --> 01:50:01,080
Speaker 1: success in the moment, which is why you've not seen

2072
01:50:01,200 --> 01:50:05,679
Speaker 1: me go many places on this story after I still

2073
01:50:05,760 --> 01:50:07,519
Speaker 1: think we don't know the end of this story yet,

2074
01:50:08,360 --> 01:50:10,760
Speaker 1: and if Iran has a nuclear weapon in the next

2075
01:50:10,800 --> 01:50:14,120
Speaker 1: two years, then this bombing campaign will be seen as

2076
01:50:14,200 --> 01:50:17,559
Speaker 1: the accelerant to them getting a nuclear weapon, and that's

2077
01:50:17,640 --> 01:50:25,160
Speaker 1: still a possibility of how this could play out. So look,

2078
01:50:26,120 --> 01:50:28,160
Speaker 1: I think that at this point, because of the way

2079
01:50:28,280 --> 01:50:31,160
Speaker 1: our media is so fragmented, how much of it is

2080
01:50:31,280 --> 01:50:33,120
Speaker 1: Trump flooding the zone and how much of it is

2081
01:50:33,120 --> 01:50:38,200
Speaker 1: our media fragmentation. But again, the collective result, if you

2082
01:50:38,360 --> 01:50:40,719
Speaker 1: just look at how he's doing politically, he's doing terribly.

2083
01:50:41,040 --> 01:50:45,040
Speaker 1: This massive big bill is just massively unpopular and growing

2084
01:50:45,120 --> 01:50:48,639
Speaker 1: more so all the time. The Iran thing isn't exactly

2085
01:50:48,720 --> 01:50:52,240
Speaker 1: pulling very well, even the modest success that it appeared

2086
01:50:52,280 --> 01:50:55,679
Speaker 1: to have at the beginning. So I take your point

2087
01:50:55,800 --> 01:51:02,160
Speaker 1: that he deserves more scrutiny or why he didn't even

2088
01:51:02,240 --> 01:51:06,320
Speaker 1: bother to go to the funeral in Minnesota, but he

2089
01:51:06,479 --> 01:51:09,200
Speaker 1: doesn't want to bring the country together. If he wanted

2090
01:51:09,240 --> 01:51:12,000
Speaker 1: to bring the country together, he would do that. But

2091
01:51:12,120 --> 01:51:15,040
Speaker 1: I think now you know he intentionally does not want

2092
01:51:15,160 --> 01:51:18,639
Speaker 1: the country to be brought together because he's politically stronger

2093
01:51:19,120 --> 01:51:20,479
Speaker 1: when we're divided.

2094
01:51:21,360 --> 01:51:22,800
Speaker 2: That is just a fact.

2095
01:51:23,960 --> 01:51:26,200
Speaker 1: Ask anybody on the right or left. When we're divided,

2096
01:51:26,760 --> 01:51:30,880
Speaker 1: that's when Donald Trump thrives something to think about. All right,

2097
01:51:31,280 --> 01:51:32,280
Speaker 1: last question and then.

2098
01:51:32,160 --> 01:51:32,920
Speaker 2: I'm gonna take a break.

2099
01:51:33,960 --> 01:51:36,160
Speaker 1: This comes from George. I'm a new listener, but love

2100
01:51:36,200 --> 01:51:38,599
Speaker 1: the show. Thanks. I was wondering what your thoughts were

2101
01:51:38,680 --> 01:51:40,760
Speaker 1: in Congress. From Mike Lawler, what do you think about

2102
01:51:40,760 --> 01:51:42,200
Speaker 1: his style of politics? Do you think he has a

2103
01:51:42,280 --> 01:51:44,000
Speaker 1: chance to win a statewide office in New York or

2104
01:51:44,080 --> 01:51:46,800
Speaker 1: rise in the Republican ranks? Thanks George, Well, I think

2105
01:51:46,880 --> 01:51:49,280
Speaker 1: his chance. I actually did think he had a I

2106
01:51:49,320 --> 01:51:51,920
Speaker 1: think he's the best possible candidate Republicans could nominate for

2107
01:51:52,000 --> 01:51:55,040
Speaker 1: governor in New York. The problem is that at least

2108
01:51:55,040 --> 01:51:57,280
Speaker 1: Stephonic wants to be governor of New York, and Trump's

2109
01:51:57,280 --> 01:52:00,160
Speaker 1: gonna endorse her, and Lawler's never going to overcome that

2110
01:52:00,200 --> 01:52:04,000
Speaker 1: Trump endorsement in a Republican primary. It doesn't matter if

2111
01:52:04,160 --> 01:52:06,040
Speaker 1: all of the polling shows that Lawler would be a

2112
01:52:06,080 --> 01:52:08,800
Speaker 1: better candidate. Lawler coming from the Hudson Valley, it's a

2113
01:52:08,920 --> 01:52:10,800
Speaker 1: much better place to run from if you're going to

2114
01:52:10,880 --> 01:52:13,040
Speaker 1: run statewide, particularly as a Republican. He knows how to

2115
01:52:13,080 --> 01:52:15,880
Speaker 1: speak to swing voters. I mean, it's the obvious play.

2116
01:52:15,960 --> 01:52:20,080
Speaker 1: At least a panic has become this Maga Darling. She

2117
01:52:20,240 --> 01:52:22,519
Speaker 1: made a choice. I'm old enough to remember when she

2118
01:52:22,720 --> 01:52:27,920
Speaker 1: was Paul Rides, a Paul Ryan acolyte. But she she

2119
01:52:28,640 --> 01:52:31,160
Speaker 1: she moved like Lindsay Graham. She found a new whale

2120
01:52:31,200 --> 01:52:35,519
Speaker 1: shark to uh To, to swim, swim near uh and

2121
01:52:35,600 --> 01:52:40,200
Speaker 1: here she is. So look, I think Lawler is the

2122
01:52:40,439 --> 01:52:43,080
Speaker 1: type of New York Republican that win New York Republicans

2123
01:52:43,080 --> 01:52:51,760
Speaker 1: win statewide. George Pataki, Albamato, they they they have the

2124
01:52:51,880 --> 01:52:55,800
Speaker 1: ideology of a Lawla very much a moderate Republican, Chamber

2125
01:52:55,800 --> 01:52:56,840
Speaker 1: of commerce Republican.

2126
01:52:57,760 --> 01:52:59,720
Speaker 2: Not a bomb thrower. In some ways, you can't be.

2127
01:52:59,800 --> 01:53:02,560
Speaker 1: If you're you're it. You know, whenever you see a

2128
01:53:02,600 --> 01:53:05,280
Speaker 1: Democrat winning a hard red in a pretty red state,

2129
01:53:05,439 --> 01:53:08,840
Speaker 1: or a Republican win in a pretty blue state, usually

2130
01:53:08,920 --> 01:53:12,320
Speaker 1: they're not bomb throwers, right, It's almost like that that's

2131
01:53:12,400 --> 01:53:14,439
Speaker 1: the you have to be in the exact opp is

2132
01:53:14,479 --> 01:53:18,040
Speaker 1: a Charlie Baker in Massachusetts, right, he had to be

2133
01:53:18,479 --> 01:53:21,759
Speaker 1: as least partisan acting as you could Bore Kelly in Kansas,

2134
01:53:21,800 --> 01:53:25,320
Speaker 1: the Democratic governor there as less partisan as you can act,

2135
01:53:25,400 --> 01:53:28,400
Speaker 1: and you know, and so I don't think you know,

2136
01:53:28,400 --> 01:53:30,439
Speaker 1: at least to phonic if you're look I think Kathy

2137
01:53:30,520 --> 01:53:33,479
Speaker 1: Holkle is as vulnerable as any incumbent Republican a Democrat

2138
01:53:33,520 --> 01:53:35,960
Speaker 1: in the country. And I think she's vulnerable to a

2139
01:53:36,000 --> 01:53:41,439
Speaker 1: Democratic primary challenge, if if only one, If she only

2140
01:53:41,479 --> 01:53:44,840
Speaker 1: faces one, she may end up facing a multi candidate

2141
01:53:44,880 --> 01:53:49,880
Speaker 1: field and she could survive that. I'm one of those

2142
01:53:49,920 --> 01:53:52,320
Speaker 1: people that thinks that Stephanic will get close but come

2143
01:53:52,400 --> 01:53:54,479
Speaker 1: up short, and that Lawler is the only one that

2144
01:53:54,520 --> 01:53:59,840
Speaker 1: could be. All right, I'm gonna pause there this, you know,

2145
01:54:00,640 --> 01:54:03,280
Speaker 1: for the month of July, just letting you know, I'm

2146
01:54:03,320 --> 01:54:07,680
Speaker 1: going to probably have one less audio drop than I've

2147
01:54:07,800 --> 01:54:10,760
Speaker 1: had throughout But who knows. Maybe I shouldn't even say

2148
01:54:10,800 --> 01:54:16,439
Speaker 1: it because news will suddenly create create more. But I

2149
01:54:16,439 --> 01:54:20,040
Speaker 1: will have probably at least one less long interview each

2150
01:54:20,120 --> 01:54:22,560
Speaker 1: week in the month of July. Then you've come to

2151
01:54:22,640 --> 01:54:24,840
Speaker 1: expect our average of three or four week we maybe

2152
01:54:24,920 --> 01:54:27,680
Speaker 1: get down to two or three a week, as I

2153
01:54:27,800 --> 01:54:29,840
Speaker 1: know everybody's gonna be traveling more and all of that.

2154
01:54:30,080 --> 01:54:32,520
Speaker 1: So I don't want to overload your system because some

2155
01:54:32,640 --> 01:54:34,640
Speaker 1: of you may sneak out and actually read a fiction

2156
01:54:34,760 --> 01:54:37,400
Speaker 1: book or two. I'll confess that I may read a

2157
01:54:37,480 --> 01:54:39,320
Speaker 1: fiction book or two because you need a break, right

2158
01:54:39,720 --> 01:54:42,560
Speaker 1: especially my friend Daniel Silva, it's got a new book out.

2159
01:54:42,640 --> 01:54:46,640
Speaker 1: I always love Gabrielle Alan, so you know I've got

2160
01:54:46,680 --> 01:54:48,880
Speaker 1: my own fiction reading list. I got to catch up

2161
01:54:48,920 --> 01:54:51,120
Speaker 1: on too, and I know you might as well. But

2162
01:54:51,240 --> 01:54:53,839
Speaker 1: I promise you we will have plenty of news updates,

2163
01:54:55,040 --> 01:54:57,240
Speaker 1: and of course we'll let you know what we've got

2164
01:54:57,360 --> 01:54:59,800
Speaker 1: new stuff up. So with that, I'll see in a

2165
01:55:00,120 --> 01:55:01,200
Speaker 1: up forty eight hours

2166
01:55:03,320 --> 01:55:03,360
Speaker 3: M